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technicolor
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HiCaD_intro_conclusion_pairs

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“Merging Results Is No Easy Task” : An International Survey Study of Collaborative Data Analysis Practices Among UX Practitioners	Usability testing is a frequently employed user-centred design method for detecting usability problems [ 25 , 110 ]. Despite being effective and useful, analyzing usability test sessions can be tedious, challenging, and time-consuming [ 12 , 25 , 29 , 81 ]. When analyzing usability test sessions, user experience (U...	We have conducted an international survey to understand the prac- tices and challenges of collaboration in the context of conducting data analysis on usability test sessions. Based on the responses of 279 participants who had varying UX experience and worked in different geographic locations, we found that UX practitio...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:“Merging Results Is No Easy Task” : An International Survey Study of Collaborative Data Analysis Practices Among UX Practitioners and the introduction:Usability testing is a frequently employed user-centred design method ...
Understanding Peer Review of Software Engineering Papers	You are invited to participate in a study entitled ”Identifying Best Practices in Peer Review” that is being conducted by Neil Ernst, Daniel Mendez, JeﬀCarver, and Marco Torchiano.	This study conducted an interview and survey-based study to understand some of the mechanisms by which reviewers in software engineering conduct reviews. We secured a large cohort of respondents derived from program committee mem- bers and journal reviewers of the past few years, many of whom have received recognition ...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:Understanding Peer Review of Software Engineering Papers and the introduction:You are invited to participate in a study entitled ”Identifying Best Practices in Peer Review” that is being conducted by Neil Ernst, Daniel Me...
Communication in Immersive Social Virtual Reality: A Systematic Review of 10 Years’ Studies	Communication is defined as the transmission of resources, such as knowledge, data, and skills, among different parties using shared symbols and media [ 12 , 62 ]. Efficient communication is an essential demand which would impact work efficiency and user experiences in contexts such as collaboration [ 64 ], social con...	Communication experiences and quality are crucial in social VR for collaboration and building social connectedness. We have con- ducted a systematic review using the PRISMA method to understand how communication has been studied in social VR in the past ten years’ published papers in the major digital libraries (i.e., ...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:Communication in Immersive Social Virtual Reality: A Systematic Review of 10 Years’ Studies and the introduction:Communication is defined as the transmission of resources, such as knowledge, data, and skills, among differ...
Deep Learning for Image Denoising: A Survey	Image processing has numerous applications including image segmentation [28], image classiﬁcation [25,38,32,12], object detection [13], video tracking [36], im- age restoration [48] and action recognition [35]. Especially, the image denoising technology is one of the most important branches of image processing technolo...	This paper ﬁrst comprehensively introduces the development of deep learning technologies on image processing applications. And then shows the implementa- tions of typical CNNs. After that, image denoising is illustrated in detail, which concludes the diﬀerences and ideas of diﬀerent methods for image denoising in real ...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:Deep Learning for Image Denoising: A Survey and the introduction:Image processing has numerous applications including image segmentation [28], image classiﬁcation [25,38,32,12], object detection [13], video tracking [36],...
Abstract	Outsourcing data storage to cloud-based services gains popularity among all kinds of users, as it seems to be a reasonable alternative to a private cloud. Cost aside, customers subordinate their choice of an adequate cloud provider to various factors, particularly availability, security, and privacy of the stored data.	In previous sections, we analyzed existing distributed storage systems provid- ing additional secrecy by use of fragmentation. We also presented database fragmentation solutions separating data in order to avoid full encryption. Few systems focus on providing a long term, secure and non-costly data storage. An- other m...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:Abstract and the introduction:Outsourcing data storage to cloud-based services gains popularity among all kinds of users, as it seems to be a reasonable alternative to a private cloud. Cost aside, customers subordinate th...
Deep Long-Tailed Learning: A Survey	D EEP learning allows computational models, composed of multiple processing layers, to learn data representations with multiple levels of abstraction [1], [2] and has made incredible progress in computer vision [3], [4], [5], [6], [7], [8]. The key enablers of deep learning are the availability of large-scale datasets...	In this survey, we have extensively reviewed classic deep long- tailed learning methods proposed before mid-2021, according to the taxonomy of class re-balancing, information augmentation and module improvement. We have empirically analyzed several state-of-the-art long-tailed methods by evaluating to what extent they ...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:Deep Long-Tailed Learning: A Survey and the introduction:D EEP learning allows computational models, composed of multiple processing layers, to learn data representations with multiple levels of abstraction [1], [2] and ...
A Survey on Cross-Lingual Summarization	To help people efﬁciently grasp the gist of docu- ments in a foreign language, Cross-Lingual Sum- marization (XLS) aims to generate a summary in the target language from the given document(s) in a different source language. This task could be re- garded as a combination of monolingual summa- rization (MS) and machine t...	In this paper, we present the ﬁrst comprehensive survey of current research efforts on XLS. We sys- tematically summarize existing XLS datasets and methods, highlight their characteristics and com- pare them with each other to provide deeper anal- yses. In addition, we give multiple perspective di- rections to facilita...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:A Survey on Cross-Lingual Summarization and the introduction:To help people efﬁciently grasp the gist of docu- ments in a foreign language, Cross-Lingual Sum- marization (XLS) aims to generate a summary in the target lang...
A Review of In-Memory Space-Eﬃcient Data Structures for Temporal Graphs	Widespread adoption of complex network concepts in information technolo- gies has driven the creation of large volumes of data to be modelled as graphs. This increasing volume of data produced at high speeds brings us new chal- lenges. On one hand, we need eﬃcient computational mechanisms to persist data that evolve co...	This paper reviewed studies about data structures for storing and querying temporal graphs in primary memory. We noted that many authors use data compression techniques to reduce the amount of space per contact needed to store temporal graphs. There are also succinct data structures that allows a variety of useful quer...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:A Review of In-Memory Space-Eﬃcient Data Structures for Temporal Graphs and the introduction:Widespread adoption of complex network concepts in information technolo- gies has driven the creation of large volumes of data t...
A Comprehensive Survey on Networking over TV White Spaces	In a historic ruling in 2008, the Federal Communication Commission (FCC) in the United States opened up the TV white space spectrum for unlicensed secondary usage [1]. TV white spaces refer to the allocated but locally unused TV channels (between 54 MHz and 698 MHz in the US). Similar regulations have been adopted by ...	The 2008 FCC ruling in the United States on TV white space spectrum has opened up new opportunities for unlicensed operation in the TV band. TV white spaces’ availability, diverse bandwidth, and excellent propagational character- istics make them suitable for long range, low-power, and large area applications such as s...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:A Comprehensive Survey on Networking over TV White Spaces and the introduction:In a historic ruling in 2008, the Federal Communication Commission (FCC) in the United States opened up the TV white space spectrum for unlice...
Towards Evaluation of Autonomously Generated Musical Compositions: A Comprehensive Survey	The scope of algorithmic composition includes a wide range of tasks, which consist of the creation of melodies, chords, rhythms or even lyrics, i.e., all the typical components of music. The purpose of this work is to present the output of the neural network without any modiﬁcations. The aim of the research is not to r...	Although we have proposed several diﬀerent methods of analytical, musicolog- ical and aesthetic evaluation, Matěj Kratochvíl’s rhetorical question from the introductory part of this paper (Kratochvíl 2020) was far from answered. Al- though the evaluation methods of musical metacreaction oﬀer several possibili- ties by ...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:Towards Evaluation of Autonomously Generated Musical Compositions: A Comprehensive Survey and the introduction:The scope of algorithmic composition includes a wide range of tasks, which consist of the creation of melodies...
A Scoping Review of Publicly Available Language Tasks in Clinical Natural Language Processing	Since the inception of the ﬁrst Integrating Biology and the Bedside (i2b2) shared task in 2006, currently known as the National Natural Language Processing (NLP) Clinical Challenge (n2c2), the ﬁeld of clinical NLP has advanced in clinical applications that rely on text from the electronic health record (EHR). Tasks wit...	The interests in introducing and participating in clinical NLP tasks are growing with more tasks surfacing each year. The breadth of tasks is also growing with topics varying from tasks with speciﬁc clinical applications to those facil- itating clinical language understanding and reasoning. It is no doubt that the ﬁeld...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:A Scoping Review of Publicly Available Language Tasks in Clinical Natural Language Processing and the introduction:Since the inception of the ﬁrst Integrating Biology and the Bedside (i2b2) shared task in 2006, currently ...
A N E XTENSIVE R EVIEW OF C OMPUTATIONAL D ANCE A UTOMATION T ECHNIQUES AND A PPLICATIONS	Efforts of combining dance and computational power can be traced back to 1967. Being a domain that needs relatively more innovation and creativity than mere following standard procedures, dance was the slowest to adopt technology. The earliest attempt was published by A. Michael Noll [2] in Dance Magazine in 1967, alth...	Creativity is considered to be a gift and no two persons can be same in this process. A ﬁeld of art like Dance is considered to be entirely a creative process although the basics are very clearly speciﬁed and taught in case of Classical Dance forms. Each choreographer is known for their particular style and creative fo...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:A N E XTENSIVE R EVIEW OF C OMPUTATIONAL D ANCE A UTOMATION T ECHNIQUES AND A PPLICATIONS and the introduction:Efforts of combining dance and computational power can be traced back to 1967. Being a domain that needs...
T WENTY - TWO YEARS SINCE REVEALING CROSS - SITE SCRIPTING ATTACKS : A SYSTEMATIC MAPPING AND A COMPREHENSIVE SURVEY	The use of web applications through the Internet has become an indispensable mean for different business and governmental organizations to reduce costs, speed up activities, improve the quality of services and reach as many targeted people as possible. Users also get immense beneﬁts from online provided services. Howev...	In this paper, we conducted a systematic mapping and a comprehensive survey studying the advancement in research to tackle XSS attacks. The study is not restricted to a period of time and covered high quality studies published since its discovery. Several studies were found in the literature but a remarkable interest i...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:T WENTY - TWO YEARS SINCE REVEALING CROSS - SITE SCRIPTING ATTACKS : A SYSTEMATIC MAPPING AND A COMPREHENSIVE SURVEY and the introduction:The use of web applications through the Internet has become an indispensable mean ...
A Deep Journey into Super-resolution: A Survey	‘Everything has been said before, but since nobody listens we have to keep going back and beginning all over again.’	Single-image super-resolution is a challenging research problem with important real-life applications. The phenom- enal success of deep learning approaches has resulted in rapid growth in deep convolutional network based tech- niques for image super-resolution. A diverse set of ap- proaches have been proposed with exci...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:A Deep Journey into Super-resolution: A Survey and the introduction:‘Everything has been said before, but since nobody listens we have to keep going back and beginning all over again.’"},{"role":"assistant","content":"Con...
Machine Learning Based Cyber Attacks Targeting on Controlled Information: A Survey	Driven by the needs to protect the enormous value within data and the evolution of the emerging data mining techniques, information leakage becomes a growing concern for governments, organizations and individuals [ 3 ]. Compromising the confidentiality of protected information is an information leakage incident and a p...	In this survey, the ML-based stealing attack against the controlled information and the defense mechanisms are reviewed. The generalized MLBSA methodology compatible with the published work is outlined. Specifically, the MLBSA methodology uncovers how adversaries steal the controlled information in five phases, i.e. ...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:Machine Learning Based Cyber Attacks Targeting on Controlled Information: A Survey and the introduction:Driven by the needs to protect the enormous value within data and the evolution of the emerging data mining technique...
Debiasing Methods for Fairer Neural Models in Vision and Language Research: A Survey	Deep Learning is a subfield of Machine Learning (ML) that leverages the capabilities of artificial neural networks to automatically learn from data. These networks are fully-differentiable computational graphs optimized via gradient descent to learn representations from raw data [ 12 ], currently being the most efficie...	In this survey paper, we have investigated debiasing methods targeting fairness-aware neural networks for language and vision research. We have contextualized fairness and its relationship with biases and their possible origins. We have presented the main metrics and evaluation measures for assessing the level of fairn...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:Debiasing Methods for Fairer Neural Models in Vision and Language Research: A Survey and the introduction:Deep Learning is a subfield of Machine Learning (ML) that leverages the capabilities of artificial neural networks ...
D EEP N EURAL N ETWORKS FOR COVID-19 D ETECTION AND D IAGNOSIS USING I MAGES AND A COUSTIC - BASED T ECHNIQUES : A R ECENT R EVIEW	The novel severe acute respiratory syndrome-related coronavirus (SARS-CoV-2) started from Wuhan, China in December 2019 and spread to all the countries worldwide. This virus caused pneumonia of unknown cytology and is named COVID-19. This infectious disease has been classiﬁed as a public health crisis of the internatio...	Although the RT-PCR test is considered the gold standard for COVID-19 diagnosis, it is time-consuming to make a decision because of high false-negative levels in the results. Therefore, medical imaging modalities such as chest X-ray and chest CT scans are the best alternative according to scientists. Chest X-ray radiog...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:D EEP N EURAL N ETWORKS FOR COVID-19 D ETECTION AND D IAGNOSIS USING I MAGES AND A COUSTIC - BASED T ECHNIQUES : A R ECENT R EVIEW and the introduction:The novel severe acute respiratory syndrome-related coronavirus...
Anaphora and Coreference Resolution: A Review	A discourse is a collocated group of sentences which convey a clear understanding only when read together. The etymology of anaphora is ana (Greek for back) and pheri (Greek for to bear), which in simple terms means repetition. In computational linguistics, anaphora is typically deﬁned as references to items mentio...	Our survey presents an exhaustive overview of the entity resolution ﬁeld, which forms a core component of natural language processing research. In this survey, we put forth a detailed account of the types of references and the important constraints for entity resolution with the aim of establishing the bread scope of t...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:Anaphora and Coreference Resolution: A Review and the introduction:A discourse is a collocated group of sentences which convey a clear understanding only when read together. The etymology of anaphora is ana (Greek for b...
Mining the online infosphere: A survey	Online infosphere 1 is the term corresponding to the Internet becoming a virtual parallel world formed from billions of networks of artiﬁcial life at diﬀerent scales ranging from tiny pieces of software to massive AI tools running a factory or driving a car. The motivations for this are diverse, seeking to both hel...	In this survey we have presented a critical rundown on the evolution of the online infosphere by depicting some of the research areas that are becoming very crucial at current times. We started our discussion with a view of the infosphere as a collaborative platform, with a dedicated focus on Wikipedia. Wikipedia, th...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:Mining the online infosphere: A survey and the introduction:Online infosphere 1 is the term corresponding to the Internet becoming a virtual parallel world formed from billions of networks of artiﬁcial life at diﬀeren...
Generalizing to Unseen Domains: A Survey on Domain Generalization	M ACHINE learning (ML) has achieved remarkable suc- cess in various areas, such as computer vision, natural language processing, and healthcare. The goal of ML is to design a model that can learn general and predictive knowledge from training data, and then apply the model to new (test) data. Traditional ML models are...	Generalization has always been an important research topic in machine learning research. In this article, we review the domain generalization areas by providing in-depth analysis of existing methods, datasets and applications. Then, we thoroughly analyze the methods. Based on our analysis, we provide several potential ...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:Generalizing to Unseen Domains: A Survey on Domain Generalization and the introduction:M ACHINE learning (ML) has achieved remarkable suc- cess in various areas, such as computer vision, natural language processing, and ...
How to Certify Machine Learning Based Safety-critical Systems?	Machine Learning (ML) is drastically changing the way we interact with the world. We are now using software applications powered by ML in critical as- pects of our daily lives; from ﬁnance, energy, to health and transportation. Thanks to frequent innovations in domains like Deep Learning (DL) and Re- inforcement Learni...	This paper provides a comprehensive overview of certiﬁcation challenges for ML based safety-critical systems. We conducted a systematic review of the literature pertaining to Robustness , Uncertainty , Explainability , Veriﬁcation , Safe Reinforcement Learning and Direct Certiﬁcation . We identiﬁed gaps in this l...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:How to Certify Machine Learning Based Safety-critical Systems? and the introduction:Machine Learning (ML) is drastically changing the way we interact with the world. We are now using software applications powered by ML in...
Recommender Systems for the Internet of Things: A Survey	Recent advances in identiﬁcation technologies, such as wireless sensor networks, RFID, and nan- otechnology, have empowered a multitude of phys- ical things with lifted computing ability [ 100 ]. Ev- eryday things have become recognizable, address- able, and controllable over the Internet. The poten- tial for seamlessl...	RSIoTs have become a crucial tool that can sup- port users in various decision-making activities. In this article, we have provided an extensive re- view of the most notable works to date on RSIoTs. We have proposed a classiﬁcation framework of three categories for the organizing and dividing of existing publications a...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:Recommender Systems for the Internet of Things: A Survey and the introduction:Recent advances in identiﬁcation technologies, such as wireless sensor networks, RFID, and nan- otechnology, have empowered a multitude of phys...
Generative Adversarial Networks: A Survey Towards Private and Secure Applications	The technological breakthrough brought by Generative Adversarial Networks (GAN) has rapidly produced a revolutionary impact on machine learning and its related fields, and this impact has already flourished to various of research areas and applications. As a powerful generative framework, GAN has significantly promoted...	This survey intensively reviews the state-of-the-art approaches using GAN for privacy and security in a broad spectrum of applications, including image generation, video event detection, records publishing, distributed learning, malware detection, fraud detection, and so on. For the different purposes of attack and def...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:Generative Adversarial Networks: A Survey Towards Private and Secure Applications and the introduction:The technological breakthrough brought by Generative Adversarial Networks (GAN) has rapidly produced a revolutionary i...
Multimodal Machine Learning: A Survey and Taxonomy	T HE world surrounding us involves multiple modalities — we see objects, hear sounds, feel texture, smell odors, and so on. In general terms, a modality refers to the way in which something happens or is experienced. Most people associate the word modality with the sensory modalities which represent our primary cha...	As part of this survey, we introduced a taxonomy of multi- modal machine learning: representation, translation, fusion, alignment, and co-learning. Some of them such as fusion have been studied for a long time, but more recent interest in representation and translation have led to a large number of new multimodal algor...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:Multimodal Machine Learning: A Survey and Taxonomy and the introduction:T HE world surrounding us involves multiple modalities — we see objects, hear sounds, feel texture, smell odors, and so on. In general terms, a mod...
A Review on Facial Micro-Expressions Analysis: Datasets, Features and Metrics	F ACIAL expression research has a long history and accel- erated through the 1970s. The modern theory on basic emotions by Ekman et al [1], [2], [3] has generated more re- search than any other in the psychology of emotion [4]. They outline 7 universal facial expressions: happy, sad, anger, fear, surprise, disgust and...	We have presented a comprehensive review on datasets, features and metrics for micro-expressions analysis. The ultimate goal of this paper is to provide new insights and recommendations to advancing the micro-expression analysis research. We have provided a good guidelines for beginners and a detailed challenges and re...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:A Review on Facial Micro-Expressions Analysis: Datasets, Features and Metrics and the introduction:F ACIAL expression research has a long history and accel- erated through the 1970s. The modern theory on basic emotions b...
A Survey among Network Operators on BGP Prefix Hijacking	BGP preﬁx hijacking 101. Autonomous Systems (ASes) use the Border Gateway Protocol (BGP) [15] to advertise address space (as IPv4/IPv6 network preﬁxes) and establish inter-domain routes in the Internet. BGP is a distributed pro- tocol, lacking authentication of advertised routes. As a re- sult, an AS is able to advert...	In this work, to increase community understanding of ex- isting BGP hijacking defenses and the needs of network op- erators, we presented the results of a survey of 75 network operators around the world.	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:A Survey among Network Operators on BGP Prefix Hijacking and the introduction:BGP preﬁx hijacking 101. Autonomous Systems (ASes) use the Border Gateway Protocol (BGP) [15] to advertise address space (as IPv4/IPv6 network...
Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey	D EEP L EARNING [1] is providing major breakthroughs in solving the problems that have withstood many attempts of machine learning and artiﬁcial intelligence com- munity in the past. As a result, it is currently being used to decipher hard scientiﬁc problems at an unprecedented scale, e.g. in reconstruction of brain ...	Deep learning is at the heart of the current rise of ma- chine learning and artiﬁcial intelligence. In the ﬁeld of Computer Vision, it has become the work horse for appli- cations ranging from self-driving cars to surveillance and security. Whereas deep neural networks have demonstrated phenomenal success (often beyond...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey and the introduction:D EEP L EARNING [1] is providing major breakthroughs in solving the problems that have withstood many attempts of machine ...
A Review of Anonymization for Healthcare Data Iyiola E. Olatunji ∗ , Jens Rauch 2 , Matthias Katzensteiner 3 , and Megha Khosla 1	With the increasing adoption of healthcare information technology (HIT) by medical institutions, the generation and capture of healthcare-related data have been increasing rapidly in the past years. The application of artiﬁcial intelligence (AI) techniques already gives a glimpse of potential improvements ranging from ...	In this paper, we provided a comprehensive review of anonymization models and techniques applicable for relational and graph-based health care data. Besides, we studied possible attacks on anonymized data and empirically demonstrated reconstruction attack on MIMIC-III data. Finally we discussed existing defense mechani...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:A Review of Anonymization for Healthcare Data Iyiola E. Olatunji ∗ , Jens Rauch 2 , Matthias Katzensteiner 3 , and Megha Khosla 1 and the introduction:With the increasing adoption of healthcare information technol...
A S URVEY AND I MPLEMENTATION OF P ERFORMANCE M ETRICS FOR S ELF -O RGANIZED M APS	Self-Organizing Maps (SOM) [ 1 ] have been used for almost 40 years across various application domains such as biology, geology, healthcare, industry [ 2 , 3 ] and humanities [ 4 ] as an interpretable tool to explore, cluster and visualize high-dimensional data sets. In every application, practitioners need to know wh...	In this paper, we reviewed various internal and external performance metrics for SOM and introduced the SOMperf Python module, enabling practitioners to easily evaluate their models. Future work perspectives include the computation of per-unit metrics, a SOM visualization module, as well as distance functions between s...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:A S URVEY AND I MPLEMENTATION OF P ERFORMANCE M ETRICS FOR S ELF -O RGANIZED M APS and the introduction:Self-Organizing Maps (SOM) [ 1 ] have been used for almost 40 years across various application domains such as b...
Meta-Learning in Neural Networks: A Survey	Contemporary machine learning models are typically trained from scratch for a speciﬁc task using a ﬁxed learn- ing algorithm designed by hand. Deep learning-based ap- proaches have seen great successes in a variety of ﬁelds [1]–[3]. However there are clear limitations [4]. For example, successes have largely been in ar...	The ﬁeld of meta-learning has recently seen a rapid growth in interest. This has come with some level of confusion, with regards to how it relates to neighbouring ﬁelds, what it can be applied to, and how it can be benchmarked. In this survey we have sought to clarify these issues by thoroughly surveying the area both ...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:Meta-Learning in Neural Networks: A Survey and the introduction:Contemporary machine learning models are typically trained from scratch for a speciﬁc task using a ﬁxed learn- ing algorithm designed by hand. Deep learning-...
An Overview of Distant Supervision for Relation Extraction with a Focus on Denoising and Pre-training Methods	Relation extraction (RE), a subtask of information extraction, is a foundational task in natural lan- guage processing (NLP). The RE task is to deter- mine a relationship between two distinct entities from text, producing fact triples in the form [ head , relation , tail ] or, as referred to in some works, [ sub- ject...	In this survey, we reviewed the relation extraction task with a focus on distant supervision. We traced the history of RE methods by discussing exemplary works and highlighting shortcomings to contextual- ize progress. We noted the key differences between pattern-based methods, statistical-based methods, neural-based m...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:An Overview of Distant Supervision for Relation Extraction with a Focus on Denoising and Pre-training Methods and the introduction:Relation extraction (RE), a subtask of information extraction, is a foundational task in n...
Scene Flow Estimation: A Survey	Scene ﬂow is a three-dimensional motion ﬁeld of the surface in world space, or in other words, it shows the three-dimensional displacement vector of each surface point between two frames. As most computer vision issues are, scene ﬂow estimation is essentially an ill-posed energy minimization problem with three unknowns...	This paper presents a comprehensive and up-to-date survey on both scene ﬂow estimation methods and the evaluation methodologies for the ﬁrst time after 17 years since scene ﬂow was introduced. We have discussed most of the estimation methods so researchers could have a clear view of this ﬁeld and get inspired for their...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:Scene Flow Estimation: A Survey and the introduction:Scene ﬂow is a three-dimensional motion ﬁeld of the surface in world space, or in other words, it shows the three-dimensional displacement vector of each surface point ...
Few-shot Learning: A Survey	“Can machines think [ 121 ]? ” This is the question raised in Alan Turing’s seminal paper entitled	Few-Shot Learning (FSL) is an important machine learning problem to facilitate real artificial intelligence. In this survey, we provide a comprehensive and systematic review of FSL. We first formally define FSL, and discuss the relatedness and difference of FSL with respect to relevant learning problems such as semi-su...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:Few-shot Learning: A Survey and the introduction:“Can machines think [ 121 ]? ” This is the question raised in Alan Turing’s seminal paper entitled"},{"role":"assistant","content":"Conclusion: Few-Shot Learning (FSL) is a...
A survey on haptic technologies for mobile augmented reality	AR and MAR have atracted interest from both industry and academia in the last decade. MAR enhances the real world of a mobile user with computer-generated virtual content. AR applications combine real and virtual objects in a physical environment, are interactive in real time and display an augmented view. Te advances ...	In this survey, we depict the state-of-the-art of several haptic devices and their capabilities as wearables in MAR ecosystem. Furthermore, we classify the haptic feedback devices by their sensory nature and their design characteristics, such as mid-air, and exoskeleton. We start with a brief description of the main fe...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:A survey on haptic technologies for mobile augmented reality and the introduction:AR and MAR have atracted interest from both industry and academia in the last decade. MAR enhances the real world of a mobile user with com...
A Uniﬁed Survey on Anomaly, Novelty, Open-Set, and Out-of-Distribution Detection: Solutions and Future Challenges	M ACHINE learning models commonly make the closed- set assumption, where the test data is drawn i.i.d from the same distribution as the training data. Yet in practice, all types of test input data—even those on which we have not trained the classiﬁer—can be encountered. Unfortunately, models can assign misleading co...	In many applications, it is not feasible to model all kinds of classes occurring during testing; thus, scenarios existing in domains such as OOD detection, OSR, ND (one-class learning), and AD become ubiquitous. Up to this time, these domains, in spite of having the same intention and a large intersection, have been fo...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:A Uniﬁed Survey on Anomaly, Novelty, Open-Set, and Out-of-Distribution Detection: Solutions and Future Challenges and the introduction:M ACHINE learning models commonly make the closed- set assumption, where the test dat...
A Brief Survey on Deep Learning Based Data Hiding, Steganography and Watermarking	Seeing is not always believing, i . e . a natural-looking image can contain secret information that is invisible to the gen- eral public. Data hiding enables concealing a secret message within a transport medium, such as a digital image, and its essential property lies in im perce pti bil it y for achieving the fu...	Deep learning based data hiding has become an emerging ﬁeld and is drawing increasing attention. Our work conducts a brief survey on this topic by ﬁrst outlining three basic meta- architectures. We further discuss the challenges of deep hid- ing in various applications, such as steganography, light ﬁeld messaging and w...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:A Brief Survey on Deep Learning Based Data Hiding, Steganography and Watermarking and the introduction:Seeing is not always believing, i . e . a natural-looking image can contain secret information that is invisible to...
A Comprehensive Survey on Automatic Knowledge Graph Construction	Knowledge graphs (KGs) provide well-organized human knowledge for applications like search engines [ 1 ], recommendation systems [ 2 ], and question answering [ 3 ].	With this paper, we delivered a comprehensive survey on the topic of knowledge graph construction. Specifically, we reviewed the tasks, methods, challenges, and related resources used to construct, refine, and integrate KGs from various data types in different scenarios. To probe into the essential topics for the big d...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:A Comprehensive Survey on Automatic Knowledge Graph Construction and the introduction:Knowledge graphs (KGs) provide well-organized human knowledge for applications like search engines [ 1 ], recommendation systems [ 2 ],...
Using Meta-heuristics and Machine Learning for Software Optimization of Parallel Computing Systems: A Systematic Literature Review	Traditionally, parallel computing [69] systems have been used for scientiﬁc and technical com- puting. Usually scientiﬁc and engineering computational problems are complex and resource intensive. To e ﬃ ciently solve these problems, utilization of parallel computing systems that may comprise multiple processing units i...	In this article, we have conducted a systematic literature review that describes approaches that use machine learning and meta-heuristics for software optimization of parallel computing systems. We have classiﬁed approaches based on the software life-cycle activities at compile-time and run-time, including the code opt...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:Using Meta-heuristics and Machine Learning for Software Optimization of Parallel Computing Systems: A Systematic Literature Review and the introduction:Traditionally, parallel computing [69] systems have been used for sci...
A Survey on Echo Chambers on Social Media: Description, Detection and Mitigation	Having access to veriﬁed and trusted information is cru- cial in the midst of the COVID-19 pandemic, one of the most signiﬁcant health crises (Mallah et al. 2021) in recent history. Exposure to misinformation on social media has been linked to COVID-19 vaccine hesitancy (Loomba et al. 2021), the belief that 5G towers s...	While the emergence of echo chambers can seem to be an unstoppable wave, we must realize that there is hope for a better information ecosystem. We showed that echo cham- bers are largely a byproduct of recommender systems. As such, what has been manufactured by these systems can like- wise be deconstructed by these sys...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:A Survey on Echo Chambers on Social Media: Description, Detection and Mitigation and the introduction:Having access to veriﬁed and trusted information is cru- cial in the midst of the COVID-19 pandemic, one of the most si...
A Systematic Literature Review of Empiricism and Norms of Reporting in Computing Education Research Literature	From 2009 to 2015, the number of bachelor’s degrees in Computer Science increased by 74 percent, while overall growth across all ﬁelds of study only rose by 16 percent [ 50 ]. Taulbee’s 2019 [ 75 ] report shows an increase from a recent minimum of under 10,000 bachelor’s degrees conferred in 2009 to over 30,000 degrees...	Our research goal was to characterize the reporting of empiricism in Computing Education Re- search literature by identifying whether publications include content necessary for researchers to perform replications, meta-analyses, and theory building. This systematic literature review sum- marizes the type of papers and ...	[{"role":"user", "content":"Help me to generate the conclusion of a survey paper given the title:A Systematic Literature Review of Empiricism and Norms of Reporting in Computing Education Research Literature and the introduction:From 2009 to 2015, the number of bachelor’s degrees in Computer Science increased by 74 p...