Check computer science papers: citations, claims and retractions

DC-YOLOv8: Small Size Object Detection Algorithm Based on Camera Sensor

Lou, H., Duan, X., Guo, J., Liu, H., Gu, J., Bi, L., & Chen, H. (2023) · Electronics

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 638

A Comprehensive Survey of Privacy-preserving Federated Learning: A Taxonomy, Review, and Future Directions

Yin, X., Zhu, Y., & Hu, J. (2022) · ACM Computing Surveys

Privacy-Preserving Technologies in DataCryptography and Data Security

Cited by 638

Large-Scale Learnable Graph Convolutional Networks

Gao, H., Wang, Z., & Ji, S. (2018) · Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

Advanced Graph Neural NetworksGraph Theory and Algorithms

Cited by 638

The SAIL databank: linking multiple health and social care datasets

Lyons, R. A., Jones, K. H., John, G., Brooks, C. J., Verplancke, J.-P., Ford, D. V., Brown, G., & Leake, K. (2009) · BMC Medical Informatics and Decision Making

Data Quality and ManagementMedical Coding and Health Information

Cited by 638

Multicenter Comparison of Machine Learning Methods and Conventional Regression for Predicting Clinical Deterioration on the Wards

Churpek, M. M., Yuen, T. C., Winslow, C., Meltzer, D. O., Kattan, M. W., & Edelson, D. P. (2016) · Critical Care Medicine

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 638

Challenges in deploying machine learning: A survey of case studies

Paleyes, A., Urma, R.-G., & Lawrence, N. D. (2023) · ACM Computing Surveys

Software Engineering Techniques and PracticesArtificial Intelligence Applications

Cited by 638

Assessment of the Suitability of Fog Computing in the Context of Internet of Things

Sarkar, S., Chatterjee, S., & Misra, S. (2018) · IEEE Transactions on Cloud Computing

IoT and Edge/Fog ComputingCloud Computing and Resource Management

Cited by 638

How Much Knowledge Can You Pack into the Parameters of a Language Model?

Roberts, A., Raffel, C., & Shazeer, N. (2020) · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

Topic ModelingInformation Retrieval and Search Behavior

Cited by 638

PUF Modeling Attacks on Simulated and Silicon Data

Ruhrmair, U., Solter, J., Sehnke, F., Xu, X., Mahmoud, A., Stoyanova, V., Dror, G., Schmidhuber, J., Burleson, W., & Devadas, S. (2013) · IEEE Transactions on Information Forensics and Security

Physical Unclonable Functions (PUFs) and Hardware SecurityCryptographic Implementations and Security

Cited by 637

GRAM: Graph-based Attention Model for Healthcare Representation Learning

Choi, E., Bahadori, M. T., Song, L., Stewart, W. F., & Sun, J. (2017) · Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 637

Research Priorities for Robust and Beneficial Artificial Intelligence

Russell, S., Dewey, D., & Tegmark, M. (2015) · AI Magazine

Ethics and Social Impacts of AIArtificial Intelligence Applications

Cited by 637

Unsupervised Cross-Lingual Representation Learning for Speech Recognition

Conneau, A., Baevski, A., Collobert, R., Mohamed, A., & Auli, M. (2021) · Interspeech 2021

Speech Recognition and SynthesisSpeech and Audio Processing

Cited by 637

Ready or not, AI comes—an interview study of organizational AI readiness factors

Jöhnk, J., Weißert, M., & Wyrtki, K. (2021) · Business & Information Systems Engineering

Artificial Intelligence ApplicationsImpact of AI and Big Data on Business and Society

Cited by 637

What Is Data Ethics?

Floridi, L., & Taddeo, M. (2016) · Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences

Ethics and Social Impacts of AIFlooding and Environmental Impact

Cited by 637

Evaluating the ε-domination based multi-objective evolutionary algorithm for a quick computation of pareto-optimal solutions

Deb, K., Mohan, M., & Mishra, S. (2005) · Evolutionary Computation

Advanced Multi-Objective Optimization AlgorithmsEvolutionary Algorithms and Applications

Cited by 637

AdapterFusion: Non-Destructive Task Composition for Transfer Learning

Pfeiffer, J., Kamath, A., Rücklé, A., Cho, K., & Gurevych, I. (2021) · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 636

AI-based pathology predicts origins for cancers of unknown primary

Lu, M. Y., Chen, T. Y., Williamson, D. F. K., Zhao, M., Shady, M., Lipkova, J., & Mahmood, F. (2021) · Nature

AI in cancer detectionCancer Diagnosis and Treatment

Cited by 636

What do we need to build explainable AI systems for the medical domain?

Holzinger, A., Biemann, C., Pattichis, C. S., & Kell, D. B. (2017) · arXiv

Explainable Artificial Intelligence (XAI)Artificial Intelligence in Healthcare and Education

Cited by 636

Ex Machina: Personal Attacks Seen at Scale

Wulczyn, E., Thain, N., & Dixon, L. (2017) · Proceedings of the 26th International Conference on World Wide Web

Hate Speech and Cyberbullying DetectionMisinformation and Its Impacts

Cited by 636

Some statistical issues in the comparison of speech recognition algorithms

Gillick, L., & Cox, S. J. (2003) · International Conference on Acoustics, Speech, and Signal Processing

Speech Recognition and SynthesisSpeech and Audio Processing

Cited by 636

Virtual reality exposure therapy in anxiety disorders: a quantitative meta-analysis

Opriş, D., Pintea, S., García-Palacios, A., Botella, C., Szamosközi, Ş., & David, D. (2012) · Depression and Anxiety

Virtual Reality Applications and ImpactsAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes

Cited by 636

Design Guidelines for Prompt Engineering Text-to-Image Generative Models

Liu, V., & Chilton, L. B. (2021) · arXiv

Generative Adversarial Networks and Image SynthesisDigital Media and Visual Art

Cited by 635

Panoptic-DeepLab: A Simple, Strong, and Fast Baseline for Bottom-Up Panoptic Segmentation

Cheng, B., Collins, M. D., Zhu, Y., Liu, T., Huang, T. S., Adam, H., & Chen, L.-C. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 635

Grover’s quantum searching algorithm is optimal

Zalka, C. (1999) · Physical Review A

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 635