Check computer science papers: citations, claims and retractions

Efficient and Side-Channel Resistant Ed25519 on ARM Cortex-M4

Owens, D., Khatib, R. E., Bisheh-Niasar, M., Azarderakhsh, R., & Kermani, M. M. (2024) · IEEE Transactions on Circuits and Systems I: Regular Papers

Cryptography and Residue ArithmeticCryptographic Implementations and Security

Cited by 58

An Analysis of Usability Evaluation Practices and Contexts of Use in Wearable Robotics

Meyer, J. T., Gassert, R., & Lambercy, O. (2021) · Journal of NeuroEngineering and Rehabilitation

Usability and User Interface DesignInnovative Human-Technology Interaction

Cited by 58

Zero Experience Required: Plug & Play Modular Transfer Learning for Semantic Visual Navigation

Al-Halah, Z., Ramakrishnan, S. K., & Grauman, K. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 58

Mobile-assisted language learning through learning analytics for self-regulated learning (MALLAS): A conceptual framework

Viberg, O., Wasson, B., & Kukulska-Hulme, A. (2020) · Australasian Journal of Educational Technology

Mobile Learning in EducationOnline Learning and Analytics

Cited by 58

Machine learning and artificial intelligence: applications in healthcare epidemiology

Hamilton, A. J., Strauss, A. T., Martinez, D. A., Hinson, J. S., Levin, S., Lin, G., & Klein, E. Y. (2021) · Antimicrobial Stewardship & Healthcare Epidemiology

Machine Learning in HealthcareArtificial Intelligence in Healthcare and Education

Cited by 58

Single image super-resolution via BM3D sparse coding

Egiazarian, K., & Katkovnik, V. (2015) · 2015 23rd European Signal Processing Conference (EUSIPCO)

Advanced Image Processing TechniquesImage and Signal Denoising Methods

Cited by 58

Human-centered AI: ensuring human control while increasing automation

Shneiderman, B. (2022) · Proceedings of the 5th Workshop on Human Factors in Hypertext

Innovative Human-Technology InteractionUsability and User Interface Design

Cited by 58

Midwives' Cell Phone Use and Health Knowledge in Rural Communities

Lee, S., Chib, A., & Kim, J.-N. (2011) · Journal of Health Communication

ICT in Developing CommunitiesMobile Health and mHealth Applications

Cited by 58

Evolutionary optimization of model merging recipes

Akiba, T., Shing, M., Tang, Y., Sun, Q., & Ha, D. (2025) · Nature Machine Intelligence

Topic ModelingNatural Language Processing Techniques

Cited by 58

Making sense of sensory input

Evans, R., Hernandez-Orallo, J., Welbl, J., Kohli, P., & Sergot, M. (2019) · arXiv

AI-based Problem Solving and PlanningBayesian Modeling and Causal Inference

Cited by 58

NIH/NCATS/GRDR® Common Data Elements: A leading force for standardized data collection

Rubinstein, Y. R., & McInnes, P. (2015) · Contemporary Clinical Trials

Research Data Management PracticesElectronic Health Records Systems

Cited by 58

Exploring Co-design with Breastfeeding Mothers

Wardle, C.-J., Green, M., Mburu, C. W., & Densmore, M. (2018) · Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems

Innovative Human-Technology InteractionUsability and User Interface Design

Cited by 58

Explainable AI and Causal Understanding: Counterfactual Approaches Considered

Baron, S. (2023) · Minds and Machines

Explainable Artificial Intelligence (XAI)Philosophy of Biology and Scientific Explanation

Cited by 58

A taxonomy of ethical, legal and social implications of wearable robots: an expert perspective

Kapeller, A., Felzmann, H., Fosch-Villaronga, E., & Hughes, A.-M. (2020) · Science and Engineering Ethics

Ethics and Social Impacts of AINeuroethics, Human Enhancement, Biomedical Innovations

Cited by 58

Co-constructing Family Memory: Understanding the Intergenerational Practices of Passing on Family Stories

Jones, J., & Ackerman, M. S. (2018) · Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems

Innovative Human-Technology InteractionIntergenerational Family Dynamics and Caregiving

Cited by 58

Applying usability heuristics to radiotherapy systems

Chan, A. J., Islam, M. K., Rosewall, T., Jaffray, D. A., Easty, A. C., & Cafazzo, J. A. (2012) · Radiotherapy and Oncology

Usability and User Interface DesignElectronic Health Records Systems

Cited by 58

Youths as targets: factors of online hate speech victimization among adolescents and young adults

Obermaier, M., & Schmuck, D. (2022) · Journal of Computer-Mediated Communication

Hate Speech and Cyberbullying DetectionBullying, Victimization, and Aggression

Cited by 58

Design and Development of SECI and Moodle Online Learning Systems to Enhance Thinking and Innovation Skills for Higher Education Learners

Chootongchai, S., & Songkram, N. (2018) · International Journal of Emerging Technologies in Learning (iJET)

Educational Technology and E-LearningOnline and Blended Learning

Cited by 58

Navigating the metric maze: a taxonomy of evaluation metrics for anomaly detection in time series

Sørbø, S., & Ruocco, M. (2024) · Data Mining and Knowledge Discovery

Anomaly Detection Techniques and ApplicationsTime Series Analysis and Forecasting

Cited by 58

Pruning vs Quantization: Which is Better?

Kuzmin, A., Nagel, M., Baalen, M. V., Behboodi, A., & Blankevoort, T. (2023) · Advances in Neural Information Processing Systems 36

Advanced Neural Network ApplicationsMachine Learning and Data Classification

Cited by 58

Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data

Kong, L., Jiang, H., Zhuang, Y., Lyu, J., Zhao, T., & Zhang, C. (2020) · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

Adversarial Robustness in Machine LearningTopic Modeling

Cited by 58

How to Address the Data Quality Issues in Regression Models: A Guided Process for Data Cleaning

Corrales, D., Corrales, J., & Ledezma, A. (2018) · Symmetry

Data Quality and ManagementMachine Learning and Data Classification

Cited by 58

Differentially private data sharing in a cloud federation with blockchain

Yang, M., Margheri, A., Hu, R., & Sassone, V. (2018) · IEEE Cloud Computing

Privacy-Preserving Technologies in DataBlockchain Technology Applications and Security

Cited by 58

Development and verification of an alcohol craving-induction tool using virtual reality: craving characteristics in social pressure situation

Cho, S., Ku, J., Park, J., Han, K., Lee, H., Choi, Y. K., Jung, Y.-C., Namkoong, K., Kim, J.-J., Kim, I. Y., et al. (2008) · CyberPsychology & Behavior

Virtual Reality Applications and ImpactsSubstance Abuse Treatment and Outcomes

Cited by 58