Check computer science papers: citations, claims and retractions

Evaluating the Validity of Current Mainstream Wearable Devices in Fitness Tracking Under Various Physical Activities: Comparative Study

Xie, J., Wen, D., Liang, L., Jia, Y., Gao, L., & Lei, J. (2018) · JMIR mHealth and uHealth

Context-Aware Activity Recognition SystemsPhysical Activity and Health

Cited by 310

On the use of AI-based tools like ChatGPT to support management research

Burger, B., Kanbach, D. K., Kraus, S., Breier, M., & Corvello, V. (2023) · European Journal of Innovation Management

Artificial Intelligence ApplicationsComputational and Text Analysis Methods

Cited by 310

Big data caching for networking: moving from cloud to edge

Zeydan, E., Bastug, E., Bennis, M., Kader, M. A., Karatepe, I. A., Er, A. S., & Debbah, M. (2016) · IEEE Communications Magazine

Caching and Content DeliveryIoT and Edge/Fog Computing

Cited by 310

PaperBench: Evaluating AI's Ability to Replicate AI Research

Starace, G., Jaffe, O., Sherburn, D., Aung, J., Chan, J. S., Maksin, L., Dias, R., Mays, E., Kinsella, B., Thompson, W., et al. (2025) · arXiv

Artificial Intelligence ApplicationsSoftware Engineering Research

Cited by 310

The ML test score: A rubric for ML production readiness and technical debt reduction

Breck, E., Cai, S., Nielsen, E., Salib, M., & Sculley, D. (2017) · 2017 IEEE International Conference on Big Data (Big Data)

Software Testing and Debugging TechniquesSoftware System Performance and Reliability

Cited by 310

SegGPT: Towards Segmenting Everything In Context

Wang, X., Zhang, X., Cao, Y., Wang, W., Shen, C., & Huang, T. (2023) · 2023 IEEE/CVF International Conference on Computer Vision (ICCV)

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 310

DAC-MACS: Effective Data Access Control for Multiauthority Cloud Storage Systems

Yang, K., Jia, X., Ren, K., Zhang, B., & Xie, R. (2013) · IEEE Transactions on Information Forensics and Security

Cryptography and Data SecurityCloud Data Security Solutions

Cited by 310

BrainMRNet: Brain tumor detection using magnetic resonance images with a novel convolutional neural network model

Toğaçar, M., Ergen, B., & Cömert, Z. (2020) · Medical Hypotheses

Brain Tumor Detection and ClassificationAI in cancer detection

Cited by 310

FedVision: An Online Visual Object Detection Platform Powered by Federated Learning

Liu, Y., Huang, A., Luo, Y., Huang, H., Liu, Y., Chen, Y., Feng, L., Chen, T., Yu, H., & Yang, Q. (2020) · Proceedings of the AAAI Conference on Artificial Intelligence

Privacy-Preserving Technologies in DataAdvanced Neural Network Applications

Cited by 310

Interaction design gone wild: striving for wild theory

Rogers, Y. (2011) · interactions

Innovative Human-Technology InteractionUsability and User Interface Design

Cited by 310

Grounding Image Matching in 3D with MASt3R

Leroy, V., Cabon, Y., & Revaud, J. (2024) · arXiv

Advanced Image and Video Retrieval TechniquesAdvanced Vision and Imaging

Cited by 309

Stakeholder identification in the requirements engineering process

Sharp, H., Finkelstein, A., & Galal, G. (1999) · Proceedings. Tenth International Workshop on Database and Expert Systems Applications. DEXA 99

Software Engineering Techniques and PracticesAdvanced Software Engineering Methodologies

Cited by 309

Multi-shot ASP solving with clingo

GEBSER, M., KAMINSKI, R., KAUFMANN, B., & SCHAUB, T. (2019) · Theory and Practice of Logic Programming

Logic, Reasoning, and KnowledgeLogic, programming, and type systems

Cited by 309

Attitudes towards AI: measurement and associations with personality

Stein, J.-P., Messingschlager, T., Gnambs, T., Hutmacher, F., & Appel, M. (2024) · Scientific Reports

Ethics and Social Impacts of AITechnology Adoption and User Behaviour

Cited by 309

Vision-Language Pre-Training with Triple Contrastive Learning

Yang, J., Duan, J., Tran, S., Xu, Y., Chanda, S., Chen, L., Zeng, B., Chilimbi, T., & Huang, J. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Multimodal Machine Learning ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 309

Software traceability: trends and future directions

Cleland-Huang, J., Gotel, O. C. Z., Huffman Hayes, J., Mäder, P., & Zisman, A. (2014) · Future of Software Engineering Proceedings

Software Engineering ResearchSoftware Engineering Techniques and Practices

Cited by 309

Deep Learning Empowered Task Offloading for Mobile Edge Computing in Urban Informatics

Zhang, K., Zhu, Y., Leng, S., He, Y., Maharjan, S., & Zhang, Y. (2019) · IEEE Internet of Things Journal

IoT and Edge/Fog ComputingEnergy Efficiency in Computing

Cited by 309

Security, Performance, and Applications of Smart Contracts: A Systematic Survey

Rouhani, S., & Deters, R. (2019) · IEEE Access

Blockchain Technology Applications and SecurityBlockchain Technology in Education and Learning

Cited by 309

Improving data transparency in clinical trials using blockchain smart contracts

Nugent, T., Upton, D., & Cimpoesu, M. (2016) · F1000Research

Blockchain Technology Applications and SecurityBlockchain Technology in Education and Learning

Cited by 309

End-to-End Instance Segmentation with Recurrent Attention

Ren, M., & Zemel, R. S. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsVisual Attention and Saliency Detection

Cited by 309

Nightmare at test time: robust learning by feature deletion

Globerson, A., & Roweis, S. (2006) · Proceedings of the 23rd international conference on Machine learning - ICML '06

Machine Learning and Data ClassificationAdversarial Robustness in Machine Learning

Cited by 309

Validity and Reliability of Wearable Sensors for Joint Angle Estimation: A Systematic Review

Poitras, I., Dupuis, F., Bielmann, M., Campeau-Lecours, A., Mercier, C., Bouyer, L., & Roy, J.-S. (2019) · Sensors

Context-Aware Activity Recognition SystemsLower Extremity Biomechanics and Pathologies

Cited by 309

MUSE: MUlti-atlas region Segmentation utilizing Ensembles of registration algorithms and parameters, and locally optimal atlas selection

Doshi, J., Erus, G., Ou, Y., Resnick, S. M., Gur, R. C., Gur, R. E., Satterthwaite, T. D., Furth, S., & Davatzikos, C. (2016) · NeuroImage

Medical Image Segmentation TechniquesMedical Imaging and Analysis

Cited by 309

Mnemonics Training: Multi-Class Incremental Learning Without Forgetting

Liu, Y., Su, Y., Liu, A.-A., Schiele, B., & Sun, Q. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 309