Check computer science papers: citations, claims and retractions

An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks

Goodfellow, I. J., Mirza, M., Xiao, D., Courville, A., & Bengio, Y. (2013) · arXiv

Domain Adaptation and Few-Shot LearningNeural Networks and Applications

Cited by 1,089

Beyond Nyquist: Efficient Sampling of Sparse Bandlimited Signals

Tropp, J. A., Laska, J. N., Duarte, M. F., Romberg, J. K., & Baraniuk, R. G. (2010) · IEEE Transactions on Information Theory

Sparse and Compressive Sensing TechniquesMathematical Analysis and Transform Methods

Cited by 1,089

Bottom-Up Object Detection by Grouping Extreme and Center Points

Zhou, X., Zhuo, J., & Krahenbuhl, P. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsVisual Attention and Saliency Detection

Cited by 1,088

Learning science in immersive virtual reality.

Parong, J., & Mayer, R. E. (2018) · Journal of Educational Psychology

Virtual Reality Applications and ImpactsVisual and Cognitive Learning Processes

Cited by 1,088

All One Needs to Know about Metaverse: A Complete Survey on Technological Singularity, Virtual Ecosystem, and Research Agenda

Lee, L.-H., Braud, T., Zhou, P., Wang, L., Xu, D., Lin, Z., Kumar, A., Bermejo, C., & Hui, P. (2021) · arXiv

Virtual Reality Applications and ImpactsAugmented Reality Applications

Cited by 1,088

Adversarial attacks on medical machine learning

Finlayson, S. G., Bowers, J. D., Ito, J., Zittrain, J. L., Beam, A. L., & Kohane, I. S. (2019) · Science

Adversarial Robustness in Machine LearningArtificial Intelligence in Healthcare and Education

Cited by 1,088

Reflexion: Language Agents with Verbal Reinforcement Learning

Shinn, N., Cassano, F., Berman, E., Gopinath, A., Narasimhan, K., & Yao, S. (2023) · arXiv

Reinforcement Learning in RoboticsSpeech and dialogue systems

Cited by 1,087

A clinically applicable approach to continuous prediction of future acute kidney injury

Tomašev, N., Glorot, X., Rae, J. W., Zielinski, M., Askham, H., Saraiva, A., Mottram, A., Meyer, C., Ravuri, S., Protsyuk, I., et al. (2019) · Nature

Machine Learning in HealthcareAcute Kidney Injury Research

Cited by 1,086

Automated breast ultrasound lesions detection using convolutional neural networks

Yap, M. H., Pons, G., Martí, J., Ganau, S., Sentís, M., Zwiggelaar, R., Davison, A. K., & Martí, R. (2018) · IEEE Journal of Biomedical and Health Informatics

AI in cancer detectionMedical Image Segmentation Techniques

Cited by 1,086

Image transformer

Parmar, N., Vaswani, A., Uszkoreit, J., Kaiser, Ł., Shazeer, N., Ku, A., & Tran, D. (2018) · arXiv

Generative Adversarial Networks and Image SynthesisAdvanced Neural Network Applications

Cited by 1,085

Algorithmic Program Debugging

Shapiro, E. Y. (1983) · The MIT Press eBooks

Software Testing and Debugging TechniquesLogic, programming, and type systems

Cited by 1,085

Federated Learning via Over-the-Air Computation

Yang, K., Jiang, T., Shi, Y., & Ding, Z. (2020) · IEEE Transactions on Wireless Communications

Privacy-Preserving Technologies in DataIoT and Edge/Fog Computing

Cited by 1,084

Predicting cancer outcomes from histology and genomics using convolutional networks

Mobadersany, P., Yousefi, S., Amgad, M., Gutman, D. A., Barnholtz-Sloan, J. S., Velázquez Vega, J. E., Brat, D. J., & Cooper, L. A. D. (2018) · Proceedings of the National Academy of Sciences

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 1,084

Power to the People: The Role of Humans in Interactive Machine Learning

Amershi, S., Cakmak, M., Knox, W. B., & Kulesza, T. (2014) · AI Magazine

Machine Learning and AlgorithmsIntelligent Tutoring Systems and Adaptive Learning

Cited by 1,084

A survey on large language model (LLM) security and privacy: The Good, The Bad, and The Ugly

Yao, Y., Duan, J., Xu, K., Cai, Y., Sun, Z., & Zhang, Y. (2024) · High-Confidence Computing

Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data

Cited by 1,083

Climbing towards NLU: On Meaning, Form, and Understanding in the Age of Data

Bender, E. M., & Koller, A. (2020) · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics

Natural Language Processing TechniquesTopic Modeling

Cited by 1,082

Predicting survival from colorectal cancer histology slides using deep learning: A retrospective multicenter study

Kather, J. N., Krisam, J., Charoentong, P., Luedde, T., Herpel, E., Weis, C.-A., Gaiser, T., Marx, A., Valous, N. A., Ferber, D., et al. (2019) · PLOS Medicine

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 1,082

The power of quantum neural networks

Abbas, A., Sutter, D., Zoufal, C., Lucchi, A., Figalli, A., & Woerner, S. (2021) · Nature Computational Science

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 1,082

E-Commerce Product Recommendation Agents: Use, Characteristics, and Impact1

Xiao, B., & Benbasat, I. (2007) · MIS Quarterly

Recommender Systems and TechniquesTechnology Adoption and User Behaviour

Cited by 1,081

TrackFormer: Multi-Object Tracking with Transformers

Meinhardt, T., Kirillov, A., Leal-Taixe, L., & Feichtenhofer, C. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Video Surveillance and Tracking MethodsAdvanced Neural Network Applications

Cited by 1,081

Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models

Samek, W., Wiegand, T., & Müller, K.-R. (2017) · arXiv

Explainable Artificial Intelligence (XAI)Software Testing and Debugging Techniques

Cited by 1,080

Feature Generating Networks for Zero-Shot Learning

Xian, Y., Lorenz, T., Schiele, B., & Akata, Z. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition

Domain Adaptation and Few-Shot LearningGenerative Adversarial Networks and Image Synthesis

Cited by 1,080

InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutions

Wang, W., Dai, J., Chen, Z., Huang, Z., Li, Z., Zhu, X., Hu, X., Lu, T., Lu, L., Li, H., et al. (2023) · 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 1,080

Visual Place Recognition: A Survey

Lowry, S., Sünderhauf, N., Newman, P., Leonard, J. J., Cox, D., Corke, P., & Milford, M. J. (2016) · IEEE Transactions on Robotics

Robotics and Sensor-Based LocalizationAdvanced Image and Video Retrieval Techniques

Cited by 1,079