Check computer science papers: citations, claims and retractions

Convergence Time Optimization for Federated Learning Over Wireless Networks

Chen, M., Poor, H. V., Saad, W., & Cui, S. (2021) · IEEE Transactions on Wireless Communications

Privacy-Preserving Technologies in DataAdvanced Wireless Network Optimization

Cited by 403

Soft-to-Hard Vector Quantization for End-to-End Learning Compressible Representations

Agustsson, E., Mentzer, F., Tschannen, M., Cavigelli, L., Timofte, R., Benini, L., & Van Gool, L. (2017) · arXiv

Advanced Data Compression TechniquesAdvanced Neural Network Applications

Cited by 403

Analysis of Explainers of Black Box Deep Neural Networks for Computer Vision: A Survey

Buhrmester, V., Münch, D., & Arens, M. (2021) · Machine Learning and Knowledge Extraction

Explainable Artificial Intelligence (XAI)Software Testing and Debugging Techniques

Cited by 403

A high-speed oscillator-based truly random number source for cryptographic applications on a smartcard IC

Bucci, M., Germani, L., Luzzi, R., Trifiletti, A., & Varanonuovo, M. (2003) · IEEE Transactions on Computers

Physical Unclonable Functions (PUFs) and Hardware SecurityAnalog and Mixed-Signal Circuit Design

Cited by 403

Youtube movie reviews: Sentiment analysis in an audio-visual context

Wollmer, M., Weninger, F., Knaup, T., Schuller, B., Sun, C., Sagae, K., & Morency, L.-P. (2013) · IEEE Intelligent Systems

Sentiment Analysis and Opinion MiningEmotion and Mood Recognition

Cited by 403

Prevalence of neural collapse during the terminal phase of deep learning training

Papyan, V., Han, X. Y., & Donoho, D. L. (2020) · Proceedings of the National Academy of Sciences

Stochastic Gradient Optimization TechniquesDomain Adaptation and Few-Shot Learning

Cited by 403

Salient Object Detection via Integrity Learning

Zhuge, M., Fan, D.-P., Liu, N., Zhang, D., Xu, D., & Shao, L. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Visual Attention and Saliency DetectionAdvanced Neural Network Applications

Cited by 403

Explanations Can Reduce Overreliance on AI Systems During Decision-Making

Vasconcelos, H., Jörke, M., Grunde-McLaughlin, M., Gerstenberg, T., Bernstein, M., & Krishna, R. (2022) · arXiv

Explainable Artificial Intelligence (XAI)Human-Automation Interaction and Safety

Cited by 403

Federated Deep Reinforcement Learning for Internet of Things With Decentralized Cooperative Edge Caching

Wang, X., Wang, C., Li, X., Leung, V. C. M., & Taleb, T. (2020) · IEEE Internet of Things Journal

Caching and Content DeliveryIoT and Edge/Fog Computing

Cited by 402

Optimizing 360 video delivery over cellular networks

Qian, F., Ji, L., Han, B., & Gopalakrishnan, V. (2016) · Proceedings of the 5th Workshop on All Things Cellular: Operations, Applications and Challenges

Image and Video Quality AssessmentCaching and Content Delivery

Cited by 402

Deep Learning is Robust to Massive Label Noise

Rolnick, D., Veit, A., Belongie, S., & Shavit, N. (2017) · arXiv

Machine Learning and Data ClassificationDomain Adaptation and Few-Shot Learning

Cited by 402

LiT: Zero-Shot Transfer with Locked-image text Tuning

Zhai, X., Wang, X., Mustafa, B., Steiner, A., Keysers, D., Kolesnikov, A., & Beyer, L. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Multimodal Machine Learning ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 402

End-to-End anti-spoofing with RawNet2

Tak, H., Patino, J., Todisco, M., Nautsch, A., Evans, N., & Larcher, A. (2021) · ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Speech Recognition and SynthesisBiometric Identification and Security

Cited by 402

A Survey on Emerging SDN and NFV Security Mechanisms for IoT Systems

Farris, I., Taleb, T., Khettab, Y., & Song, J. (2019) · IEEE Communications Surveys & Tutorials

Software-Defined Networks and 5GIoT and Edge/Fog Computing

Cited by 402

Massively Multilingual Neural Machine Translation

Aharoni, R., Johnson, M., & Firat, O. (2019) · Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)

Natural Language Processing TechniquesTopic Modeling

Cited by 402

A cloud detection algorithm for satellite imagery based on deep learning

Jeppesen, J. H., Jacobsen, R. H., Inceoglu, F., & Toftegaard, T. S. (2019) · Remote Sensing of Environment

Remote-Sensing Image ClassificationSatellite Image Processing and Photogrammetry

Cited by 402

Being Barbie: the size of one’s own body determines the perceived size of the world.

van der Hoort, B., Guterstam, A., & Ehrsson, H. H. (2011) · PLoS ONE

Virtual Reality Applications and ImpactsVisual perception and processing mechanisms

Cited by 402

Clustering-Based Speech Emotion Recognition by Incorporating Learned Features and Deep BiLSTM

Mustaqeem, Sajjad, M., & Kwon, S. (2020) · IEEE Access

Emotion and Mood RecognitionSpeech Recognition and Synthesis

Cited by 402

Real-time part-based visual tracking via adaptive correlation filters

Liu, T., Wang, G., & Yang, Q. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Video Surveillance and Tracking MethodsAdvanced Image and Video Retrieval Techniques

Cited by 402

Explanations Can Reduce Overreliance on AI Systems During Decision-Making

Vasconcelos, H., Jörke, M., Grunde-McLaughlin, M., Gerstenberg, T., Bernstein, M. S., & Krishna, R. (2023) · Proceedings of the ACM on Human-Computer Interaction

Explainable Artificial Intelligence (XAI)Human-Automation Interaction and Safety

Cited by 402

Low Resource Dependency Parsing: Cross-lingual Parameter Sharing in a Neural Network Parser

Duong, L., Cohn, T., Bird, S., & Cook, P. (2015) · Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)

Natural Language Processing TechniquesSyntax, Semantics, Linguistic Variation

Cited by 402

Discrimination in the Age of Algorithms

Kleinberg, J., Ludwig, J., Mullainathan, S., & Sunstein, C. R. (2018) · Journal of Legal Analysis

Ethics and Social Impacts of AIDiscrimination and Equality Law

Cited by 401

Large-Scale Study of Curiosity-Driven Learning

Burda, Y., Edwards, H., Pathak, D., Storkey, A., Darrell, T., & Efros, A. A. (2018) · arXiv

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 401

Human language reveals a universal positivity bias

Dodds, P. S., Clark, E. M., Desu, S., Frank, M. R., Reagan, A. J., Williams, J. R., Mitchell, L., Harris, K. D., Kloumann, I. M., Bagrow, J. P., et al. (2015) · Proceedings of the National Academy of Sciences

Sentiment Analysis and Opinion MiningEmotion and Mood Recognition

Cited by 401