Check computer science papers: citations, claims and retractions

Epigraphics: Message-Driven Infographics Authoring

Zhou, T., Huang, J., & Chan, G. Y.-Y. (2024) · Proceedings of the CHI Conference on Human Factors in Computing Systems

Data Visualization and AnalyticsDigital Media and Visual Art

Cited by 17

Quantum Technologies: Digital Transformation, Social Impact, and Cross-sector Disruption

Allende López, M., & Da Silva, M. M. (2019)

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 17

Designing Out Stereotypes in Artificial Intelligence: Involving users in the personality design of a digital assistant

Spencer, J., Poggi, J., & Gheerawo, R. (2018) · Proceedings of the 4th EAI International Conference on Smart Objects and Technologies for Social Good

Ethics and Social Impacts of AIAI in Service Interactions

Cited by 17

BapFL: You can Backdoor Personalized Federated Learning

Ye, T., Chen, C., Wang, Y., Li, X., & Gao, M. (2024) · ACM Transactions on Knowledge Discovery from Data

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 17

Artificial intelligence in Dermatopathology

Jartarkar, S. R., Cockerell, C. J., Patil, A., Kassir, M., Babaei, M., Weidenthaler‐Barth, B., Grabbe, S., & Goldust, M. (2023) · Journal of Cosmetic Dermatology

AI in cancer detectionArtificial Intelligence in Healthcare and Education

Cited by 17

IoT Data Quality Assessment Framework Using Adaptive Weighted Estimation Fusion

Byabazaire, J., O’Hare, G. M. P., Collier, R., & Delaney, D. (2023) · Sensors

Data Quality and ManagementMobile Crowdsensing and Crowdsourcing

Cited by 17

Moderator effects of mobile users’ pedagogical role on science learning: a meta-analysis.

Shi, L., & Kopcha, T. J. (2022) · British Journal of Educational Technology

Mobile Learning in EducationScience Education and Pedagogy

Cited by 17

Generating Is Believing: Membership Inference Attacks against Retrieval-Augmented Generation

Li, Y., Liu, G., Wang, C., & Yang, Y. (2024) · arXiv

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 17

A Novel Singular Value Decomposition-Based Denoising Method in 4-Dimensional Computed Tomography of the Brain in Stroke Patients with Statistical Evaluation

Yang, W., Hong, J.-Y., Kim, J.-Y., Paik, S.-H., Lee, S. H., Park, J.-S., Lee, G., Kim, B. M., & Jung, Y.-J. (2020) · Sensors

Image and Signal Denoising MethodsMedical Imaging Techniques and Applications

Cited by 17

Yolo-Based Traffic Sign Recognition Algorithm

Li, M., Zhang, L., Li, L., & Song, W. (2022) · Computational Intelligence and Neuroscience

Advanced Neural Network ApplicationsAutonomous Vehicle Technology and Safety

Cited by 17

Towards Trustworthy AI in Healthcare: Epistemic Uncertainty Estimation for Clinical Decision Support

Lindenmeyer, A., Blattmann, M., Franke, S., Neumuth, T., & Schneider, D. (2025) · Journal of Personalized Medicine

Machine Learning in HealthcareArtificial Intelligence in Healthcare and Education

Cited by 17

Partially Generative Neural Networks for Gang Crime Classification with Partial Information

Seo, S., Chan, H., Brantingham, P. J., Leap, J., Vayanos, P., Tambe, M., & Liu, Y. (2018) · Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society

Data Mining and Machine Learning ApplicationsCrime Patterns and Interventions

Cited by 17

Neural gradients are near-lognormal: improved quantized and sparse training

Chmiel, B., Ben-Uri, L., Shkolnik, M., Hoffer, E., Banner, R., & Soudry, D. (2020) · arXiv

Advanced Neural Network ApplicationsStochastic Gradient Optimization Techniques

Cited by 17

Debiasing isn't enough! -- On the Effectiveness of Debiasing MLMs and their Social Biases in Downstream Tasks

Kaneko, M., Bollegala, D., & Okazaki, N. (2022) · arXiv

Ethics and Social Impacts of AITopic Modeling

Cited by 17

Prefix Conditioning Unifies Language and Label Supervision

Saito, K., Sohn, K., Zhang, X., Li, C.-L., Lee, C.-Y., Saenko, K., & Pfister, T. (2022) · arXiv

Multimodal Machine Learning ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 17

Towards optimal outsourcing of service function chain across multiple clouds

Chen, H., Xu, S., Wang, X., Zhao, Y., Li, K., Wang, Y., Wang, W., & Li, L. M. (2016) · 2016 IEEE International Conference on Communications (ICC)

Software-Defined Networks and 5GCloud Computing and Resource Management

Cited by 17

SBFL-Suitability: A Software Characteristic for Fault Localization

Sasaki, Y., Higo, Y., Matsumoto, S., & Kusumoto, S. (2020) · 2020 IEEE International Conference on Software Maintenance and Evolution (ICSME)

Software Testing and Debugging TechniquesSoftware Engineering Research

Cited by 17

Automated segmentation and measurement of the female pelvic floor from the mid-sagittal plane of 3D ultrasound volumes

Szentimrey, Z., Ameri, G., Hong, C. X., Cheung, R. Y. K., Ukwatta, E., & Eltahawi, A. (2023) · Medical Physics

Medical Image Segmentation TechniquesPelvic floor disorders treatments

Cited by 17

What's in the Box? A Preliminary Analysis of Undesirable Content in the Common Crawl Corpus

Luccioni, A. S., & Viviano, J. D. (2021) · arXiv

Hate Speech and Cyberbullying DetectionTopic Modeling

Cited by 17

Self-tuning Database Systems: A Systematic Literature Review of Automatic Database Schema Design and Tuning

Mozaffari, M., Dignös, A., Gamper, J., & Störl, U. (2024) · ACM Computing Surveys

Advanced Database Systems and QueriesCloud Computing and Resource Management

Cited by 17

Deep learning for Amazon satellite image analysis

Bragilevsky, L., & Bajic, I. V. (2017) · 2017 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM)

Remote-Sensing Image ClassificationRemote Sensing in Agriculture

Cited by 17

Shake before building: replacing make with haskell

Mitchell, N. (2012) · Proceedings of the 17th ACM SIGPLAN international conference on Functional programming

Logic, programming, and type systemsSoftware Engineering Techniques and Practices

Cited by 17

“I’m Not a Number, I’m Someone to Them”: Supporting Commencing University Students’ Through Technology-Mediated Personalised Communication

Lewis, S., Heath, G., Lim, L., & Roberts, R. (2021) · Student Success

Online Learning and AnalyticsHigher Education Research Studies

Cited by 17

Investigating the Effects of Word Substitution Errors on Sentence Embeddings

Voleti, R., Liss, J. M., & Berisha, V. (2019) · ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Topic ModelingSpeech Recognition and Synthesis

Cited by 17