Check computer science papers: citations, claims and retractions

Multiclass semantic segmentation and quantification of traumatic brain injury lesions on head CT using deep learning: an algorithm development and multicentre validation study

Monteiro, M., Newcombe, V. F. J., Mathieu, F., Adatia, K., Kamnitsas, K., Ferrante, E., Das, T., Whitehouse, D., Rueckert, D., Menon, D. K., et al. (2020) · The Lancet Digital Health

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 162

On Circuit-Based Hybrid Quantum Neural Networks for Remote Sensing Imagery Classification

Sebastianelli, A., Zaidenberg, D. A., Spiller, D., Le Saux, B., & Ullo, S. (2022) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Quantum Computing Algorithms and ArchitectureRemote-Sensing Image Classification

Cited by 162

Boosting Deep Learning Risk Prediction with Generative Adversarial Networks for Electronic Health Records

Che, Z., Cheng, Y., Zhai, S., Sun, Z., & Liu, Y. (2017) · 2017 IEEE International Conference on Data Mining (ICDM)

Machine Learning in HealthcareArtificial Intelligence in Healthcare and Education

Cited by 162

Dynamic Graph Learning with Content-guided Spatial-Frequency Relation Reasoning for Deepfake Detection

Wang, Y., Yu, K., Chen, C., Hu, X., & Peng, S. (2023) · 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Digital Media Forensic DetectionGenerative Adversarial Networks and Image Synthesis

Cited by 161

Design and Development of a Multimodal Biomedical Information Retrieval System

Demner-Fushman, D., Antani, S., Simpson, M., & Thoma, G. R. (2012) · Journal of Computing Science and Engineering

Image Retrieval and Classification TechniquesInformation Retrieval and Search Behavior

Cited by 161

Virtual Reality Therapy: an Effective Treatment for the Fear of Public Speaking

North, M. M., North, S. M., & Coble, J. R. (1998) · International Journal of Virtual Reality

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

Cited by 161

Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation

Press, O., Smith, N. A., & Lewis, M. (2021) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 161

Few-Shot Class-Incremental Learning via Relation Knowledge Distillation

Dong, S., Hong, X., Tao, X., Chang, X., Wei, X., & Gong, Y. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 161

Fairness and Explanation in AI-Informed Decision Making

Angerschmid, A., Zhou, J., Theuermann, K., Chen, F., & Holzinger, A. (2022) · Machine Learning and Knowledge Extraction

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 161

ForgeryNet: A Versatile Benchmark for Comprehensive Forgery Analysis

He, Y., Gan, B., Chen, S., Zhou, Y., Yin, G., Song, L., Sheng, L., Shao, J., & Liu, Z. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Digital Media Forensic DetectionGenerative Adversarial Networks and Image Synthesis

Cited by 161

The Evolution of an ICT Platform-Enabled Ecosystem for Poverty Alleviation: The Case of Ekutir1

Jha, S. K., Pinsonneault, A., & Dubé, L. (2016) · MIS Quarterly

ICT in Developing CommunitiesDigital Platforms and Economics

Cited by 161

Assessing the communication gap between AI models and healthcare professionals: explainability, utility and trust in AI-driven clinical decision-making

Wysocki, O., Davies, J. K., Vigo, M., Armstrong, A. C., Landers, D., Lee, R., & Freitas, A. (2023) · Artificial Intelligence

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

Cited by 161

Hospital Readmission and Social Risk Factors Identified from Physician Notes

Navathe, A. S., Zhong, F., Lei, V. J., Chang, F. Y., Sordo, M., Topaz, M., Navathe, S. B., Rocha, R. A., & Zhou, L. (2018) · Health Services Research

Machine Learning in HealthcareMedical Coding and Health Information

Cited by 161

Runaway Feedback Loops in Predictive Policing

Ensign, D., Friedler, S. A., Neville, S., Scheidegger, C., & Venkatasubramanian, S. (2017) · arXiv

Ethics and Social Impacts of AIPolicing Practices and Perceptions

Cited by 161

Feasibility of Reidentifying Individuals in Large National Physical Activity Data Sets From Which Protected Health Information Has Been Removed With Use of Machine Learning

Na, L., Yang, C., Lo, C.-C., Zhao, F., Fukuoka, Y., & Aswani, A. (2018) · JAMA Network Open

Privacy-Preserving Technologies in DataThoreau and American Literature

Cited by 161

Weight Agnostic Neural Networks

Gaier, A., & Ha, D. (2019) · Unpublished

Neural Networks and ApplicationsAdvanced Neural Network Applications

Cited by 161

Language Models with Transformers

Wang, C., Li, M., & Smola, A. J. (2019) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 161

Fault-tolerant quantum computation with cluster states

Nielsen, M. A., & Dawson, C. M. (2005) · Physical Review A

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 161

Attention Based Fully Convolutional Network for Speech Emotion Recognition

Zhang, Y., Du, J., Wang, Z., Zhang, J., & Tu, Y. (2018) · 2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)

Emotion and Mood RecognitionSpeech Recognition and Synthesis

Cited by 161

fpgaConvNet: Mapping regular and irregular convolutional neural networks on FPGAs

Venieris, S. I., & Bouganis, C.-S. (2019) · IEEE Transactions on Neural Networks and Learning Systems

Embedded Systems Design TechniquesAdvanced Neural Network Applications

Cited by 161

Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion

Buckman, J., Hafner, D., Tucker, G., Brevdo, E., & Lee, H. (2018) · arXiv

Reinforcement Learning in RoboticsAdaptive Dynamic Programming Control

Cited by 161

Knowledge Graph Based Synthetic Corpus Generation for Knowledge-Enhanced Language Model Pre-training

Agarwal, O., Ge, H., Shakeri, S., & Al-Rfou, R. (2021) · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Topic ModelingNatural Language Processing Techniques

Cited by 161

Algorithmic realism: expanding the boundaries of algorithmic thought

Green, B., & Viljoen, S. (2020) · Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency

Ethics and Social Impacts of AIArtificial Intelligence in Law

Cited by 161

Online domain adaptation of a pre-trained cascade of classifiers

Jain, V., & Learned-Miller, E. (2011) · CVPR 2011

Domain Adaptation and Few-Shot LearningFace recognition and analysis

Cited by 161