Check computer science papers: citations, claims and retractions

Federated Unlearning via Class-Discriminative Pruning

Wang, J., Guo, S., Xie, X., & Qi, H. (2022) · Proceedings of the ACM Web Conference 2022

Privacy-Preserving Technologies in DataDomain Adaptation and Few-Shot Learning

Cited by 157

Updates-Leak: Data Set Inference and Reconstruction Attacks in Online Learning

Salem, A., Bhattacharya, A., Backes, M., Fritz, M., & Zhang, Y. (2020) · Universität des Saarlandes

Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data

Cited by 157

Cost-Aware Dynamic SFC Mapping and Scheduling in SDN/NFV-Enabled Space–Air–Ground-Integrated Networks for Internet of Vehicles

Li, J., Shi, W., Wu, H., Zhang, S., & Shen, X. (2022) · IEEE Internet of Things Journal

Software-Defined Networks and 5GSatellite Communication Systems

Cited by 157

capAI - A Procedure for Conducting Conformity Assessment of AI Systems in Line with the EU Artificial Intelligence Act

Floridi, L., Holweg, M., Taddeo, M., Amaya, J., Mökander, J., & Wen, Y. (2022) · SSRN Electronic Journal

Ethics and Social Impacts of AIDigitalization, Law, and Regulation

Cited by 157

Is Virtual Reality Effective in Orthopedic Rehabilitation? A Systematic Review and Meta-Analysis

Gumaa, M., & Rehan Youssef, A. (2019) · Physical Therapy

Virtual Reality Applications and ImpactsStroke Rehabilitation and Recovery

Cited by 157

Segmentation and tracking of faces in color images

Sobottka, K., & Pitas, I. (2002) · Proceedings of the Second International Conference on Automatic Face and Gesture Recognition

Face recognition and analysisFace and Expression Recognition

Cited by 157

PromptMaker: Prompt-based Prototyping with Large Language Models

Jiang, E., Olson, K., Toh, E., Molina, A., Donsbach, A., Terry, M., & Cai, C. J. (2022) · CHI Conference on Human Factors in Computing Systems Extended Abstracts

Usability and User Interface DesignSoftware Engineering Techniques and Practices

Cited by 157

Variational Bayes for generalized autoregressive models

Roberts, S. J., & Penny, W. D. (2002) · IEEE Transactions on Signal Processing

Bayesian Methods and Mixture ModelsControl Systems and Identification

Cited by 157

Real-time object detection based on YOLO-v2 for tiny vehicle object

Han, X., Chang, J., & Wang, K. (2021) · Procedia Computer Science

Advanced Neural Network ApplicationsAutonomous Vehicle Technology and Safety

Cited by 157

Effective test generation using pre-trained Large Language Models and mutation testing

Dakhel, A. M., Nikanjam, A., Majdinasab, V., Khomh, F., & Desmarais, M. C. (2024) · Information and Software Technology

Software Testing and Debugging TechniquesSoftware Engineering Research

Cited by 157

Adversarial Video Generation on Complex Datasets

Clark, A., Donahue, J., & Simonyan, K. (2019) · arXiv

Generative Adversarial Networks and Image SynthesisDigital Media Forensic Detection

Cited by 157

Internet of Video Things: Next-Generation IoT With Visual Sensors

Chen, C. W. (2020) · IEEE Internet of Things Journal

IoT and Edge/Fog ComputingInternet of Things and AI

Cited by 157

Muse: Text-To-Image Generation via Masked Generative Transformers

Chang, H., Zhang, H., Barber, J., Maschinot, A., Lezama, J., Jiang, L., Yang, M.-H., Murphy, K., Freeman, W. T., Rubinstein, M., et al. (2023) · arXiv

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 157

Automated muscle segmentation from clinical CT using Bayesian U-net for personalized musculoskeletal modeling

Hiasa, Y., Otake, Y., Takao, M., Ogawa, T., Sugano, N., & Sato, Y. (2020) · IEEE Transactions on Medical Imaging

Medical Image Segmentation TechniquesMedical Imaging and Analysis

Cited by 157

DropConnect Is Effective in Modeling Uncertainty of Bayesian Deep Networks

Mobiny, A., Nguyen, H. V., Moulik, S., Garg, N., & Wu, C. C. (2019) · arXiv

Gaussian Processes and Bayesian InferenceAdversarial Robustness in Machine Learning

Cited by 157

Classification of breast cancer in ultrasound imaging using a generic deep learning analysis software: a pilot study

Becker, A. S., Mueller, M., Stoffel, E., Marcon, M., Ghafoor, S., & Boss, A. (2018) · The British Journal of Radiology

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 157

Tree-to-tree neural networks for program translation

Chen, X., Liu, C., & Song, D. (2018) · arXiv

Software Engineering ResearchNatural Language Processing Techniques

Cited by 157

Applications of Federated Learning; Taxonomy, Challenges, and Research Trends

Shaheen, M., Farooq, M. S., Umer, T., & Kim, B.-S. (2022) · Electronics

Privacy-Preserving Technologies in DataIoT and Edge/Fog Computing

Cited by 157

Generative Pre-Training for Speech with Autoregressive Predictive Coding

Chung, Y.-A., & Glass, J. (2020) · ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Speech Recognition and SynthesisSpeech and Audio Processing

Cited by 157

Yao.jl: Extensible, Efficient Framework for Quantum Algorithm Design

Luo, X.-Z., Liu, J.-G., Zhang, P., & Wang, L. (2020) · Quantum

Quantum Computing Algorithms and ArchitectureParallel Computing and Optimization Techniques

Cited by 157

The Benefits of emotion Regulation Interventions in Virtual Reality for the Improvement of Wellbeing in Adults and Older Adults: A Systematic Review

Montana, J. I., Matamala-Gomez, M., Maisto, M., Mavrodiev, P. A., Cavalera, C. M., Diana, B., Mantovani, F., & Realdon, O. (2020) · Journal of Clinical Medicine

Virtual Reality Applications and ImpactsDigital Mental Health Interventions

Cited by 156

Designing for human–AI complementarity in K‐12 education

Holstein, K., & Aleven, V. (2022) · AI Magazine

Intelligent Tutoring Systems and Adaptive LearningArtificial Intelligence in Education

Cited by 156

Layers of bias: A unified approach for understanding problems with risk assessment

Eckhouse, L., Lum, K., Conti-Cook, C., & Ciccolini, J. (2019) · Criminal Justice and Behavior

Ethics and Social Impacts of AICriminal Justice and Corrections Analysis

Cited by 156

Explainable Agency for Intelligent Autonomous Systems

Langley, P., Meadows, B., Sridharan, M., & Choi, D. (2017) · Proceedings of the AAAI Conference on Artificial Intelligence

Explainable Artificial Intelligence (XAI)AI-based Problem Solving and Planning

Cited by 156