Check computer science papers: citations, claims and retractions

Comprehensive testing of large language models for extraction of structured data in pathology

Grothey, B., Odenkirchen, J., Brkic, A., Schömig-Markiefka, B., Quaas, A., Büttner, R., & Tolkach, Y. (2025) · Communications Medicine

Machine Learning in HealthcareBiomedical Text Mining and Ontologies

Cited by 54

Exploring ELM-based spatial–spectral classification of hyperspectral images

Heras, D. B., Argüello, F., & Quesada-Barriuso, P. (2014) · International Journal of Remote Sensing

Remote-Sensing Image ClassificationMachine Learning and ELM

Cited by 54

Preparation of many-body states for quantum simulation

Ward, N. J., Kassal, I., & Aspuru-Guzik, A. (2009) · The Journal of Chemical Physics

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 54

Exploring autonomous methods for deepfake detection: A detailed survey on techniques and evaluation

Sunil, R., Mer, P., Diwan, A., Mahadeva, R., & Sharma, A. (2025) · Heliyon

Digital Media Forensic DetectionMisinformation and Its Impacts

Cited by 54

Experiences with an AR evaluation test bed: Presence, performance, and physiological measurement

Gandy, M., Catrambone, R., MacIntyre, B., Alvarez, C., Eiriksdottir, E., Hilimire, M., Davidson, B., & McLaughlin, A. C. (2010) · 2010 IEEE International Symposium on Mixed and Augmented Reality

Virtual Reality Applications and ImpactsAugmented Reality Applications

Cited by 54

Object Detection for Autonomous Vehicles with Sensor-based Technology Using YOLO

Dazlee, N. M. A. A., Khalil, S. A., Abdul-Rahman, S., & Mutalib, S. (2022) · International Journal of Intelligent Systems and Applications in Engineering

Advanced Neural Network ApplicationsAutonomous Vehicle Technology and Safety

Cited by 54

SpoC: Spoofing Camera Fingerprints

Cozzolino, D., Thies, J., Rossler, A., Niesner, M., & Verdoliva, L. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Digital Media Forensic DetectionAdvanced Steganography and Watermarking Techniques

Cited by 54

Product1M: Towards Weakly Supervised Instance-Level Product Retrieval via Cross-Modal Pretraining

Zhan, X., Wu, Y., Dong, X., Wei, Y., Lu, M., Zhang, Y., Xu, H., & Liang, X. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Multimodal Machine Learning ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 54

Catastrophic Forgetting in Deep Learning: A Comprehensive Taxonomy

Aleixo, E. L., Colonna, J. G., Cristo, M., & Fernandes, E. (2023) · arXiv

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 54

Jatmo: Prompt Injection Defense by Task-Specific Finetuning

Piet, J., Alrashed, M., Sitawarin, C., Chen, S., Wei, Z., Sun, E., Alomair, B., & Wagner, D. (2023) · arXiv

Adversarial Robustness in Machine LearningTopic Modeling

Cited by 54

Deconvolution of Serum Cortisol Levels by Using Compressed Sensing

Faghih, R. T., Dahleh, M. A., Adler, G. K., Klerman, E. B., & Brown, E. N. (2014) · PLoS ONE

Sparse and Compressive Sensing TechniquesAdrenal Hormones and Disorders

Cited by 54

Continual Learning in Low-rank Orthogonal Subspaces

Chaudhry, A., Khan, N., Dokania, P. K., & Torr, P. H. S. (2020) · arXiv

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 54

Continuous Multimodal Emotion Prediction Based on Long Short Term Memory Recurrent Neural Network

Huang, J., Li, Y., Tao, J., Lian, Z., Wen, Z., Yang, M., & Yi, J. (2017) · Proceedings of the 7th Annual Workshop on Audio/Visual Emotion Challenge

Emotion and Mood RecognitionSpeech and Audio Processing

Cited by 54

Young Children Can Learn Scientific Reasoning with Teachable Agents

Chin, D. B., Dohmen, I. M., & Schwartz, D. L. (2013) · IEEE Transactions on Learning Technologies

Intelligent Tutoring Systems and Adaptive LearningScience Education and Pedagogy

Cited by 54

Caching in Base Station with Recommendation via Q-Learning

Guo, K., Yang, C., & Liu, T. (2017) · 2017 IEEE Wireless Communications and Networking Conference (WCNC)

Caching and Content DeliveryIoT and Edge/Fog Computing

Cited by 54

Towards a pragmatist dealing with algorithmic bias in medical machine learning

Starke, G., De Clercq, E., & Elger, B. S. (2021) · Medicine, Health Care and Philosophy

Ethics and Social Impacts of AIArtificial Intelligence in Healthcare and Education

Cited by 54

Relativistic effects and rigorous limits for discrete- and continuous-time quantum walks

Strauch, F. W. (2007) · Journal of Mathematical Physics

Quantum Computing Algorithms and ArchitectureQuantum Mechanics and Applications

Cited by 54

Helpful, harmless, honest? Sociotechnical limits of AI alignment and safety through Reinforcement Learning from Human Feedback

Dahlgren Lindström, A., Methnani, L., Krause, L., Ericson, P., de Rituerto de Troya, Í. M., Coelho Mollo, D., & Dobbe, R. (2025) · Ethics and Information Technology

Ethics and Social Impacts of AISafety Systems Engineering in Autonomy

Cited by 54

Re-examining the quantum volume test: Ideal distributions, compiler optimizations, confidence intervals, and scalable resource estimations

Baldwin, C. H., Mayer, K., Brown, N. C., Ryan-Anderson, C., & Hayes, D. (2022) · Quantum

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 54

Learning Continuous Control Actions for Robotic Grasping with Reinforcement Learning

Shahid, A. A., Roveda, L., Piga, D., & Braghin, F. (2020) · 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 54

THE EFFECTIVENESS OF THE USE OF E-LEARNING IN MULTIMEDIA CLASSES TO IMPROVE VOCATIONAL STUDENTS' LEARNING ACHIEVEMENT AND MOTIVATION

Hoerunnisa, A., Suryani, N., & Efendi, A. (2019) · Kwangsan: Jurnal Teknologi Pendidikan

Educational Technology and E-LearningTechnology-Enhanced Education Studies

Cited by 54

Averaging Is Probably Not the Optimum Way of Aggregating Parameters in Federated Learning

Xiao, P., Cheng, S., Stankovic, V., & Vukobratovic, D. (2020) · Entropy

Privacy-Preserving Technologies in DataStochastic Gradient Optimization Techniques

Cited by 54

Workflow-Aware Automatic Fault Diagnosis for Microservice-Based Applications With Statistics

Wang, T., Zhang, W., Xu, J., & Gu, Z. (2020) · IEEE Transactions on Network and Service Management

Software System Performance and ReliabilitySoftware Testing and Debugging Techniques

Cited by 54

HiHAR: A Hierarchical Hybrid Deep Learning Architecture for Wearable Sensor-Based Human Activity Recognition

Hoai Thu, N. T., & Han, D. S. (2021) · IEEE Access

Context-Aware Activity Recognition SystemsTime Series Analysis and Forecasting

Cited by 54