Check computer science papers: citations, claims and retractions

Analysis of identity management systems using blockchain technology

Haddouti, S. E., & Ech-Cherif El Kettani, M. D. (2019) · 2019 International Conference on Advanced Communication Technologies and Networking (CommNet)

Blockchain Technology Applications and SecurityBlockchain Technology in Education and Learning

Cited by 106

Secret Collusion among AI Agents: Multi-Agent Deception via Steganography

Motwani, S., Baranchuk, M., Strohmeier, M., Bolina, V., Torr, P., Hammond, L., & Witt, C. D. (2024) · Advances in Neural Information Processing Systems 37

Adversarial Robustness in Machine LearningAdvanced Steganography and Watermarking Techniques

Cited by 106

An Evaluation of an Adaptive Learning System Based on Multimodal Affect Recognition for Learners with Intellectual Disabilities

Standen, P. J., Brown, D. J., Taheri, M., Galvez Trigo, M. J., Boulton, H., Burton, A., Hallewell, M. J., Lathe, J. G., Shopland, N., Blanco Gonzalez, M. A., et al. (2020) · British Journal of Educational Technology

Intelligent Tutoring Systems and Adaptive LearningOnline Learning and Analytics

Cited by 106

Data-image-video encryption

Yang, M., Bourbakis, N., & Li, S. (2004) · IEEE Potentials

Chaos-based Image/Signal EncryptionAdvanced Steganography and Watermarking Techniques

Cited by 105

Pixel-Based Image Encryption Without Key Management for Privacy-Preserving Deep Neural Networks

Sirichotedumrong, W., Kinoshita, Y., & Kiya, H. (2019) · IEEE Access

Chaos-based Image/Signal EncryptionCryptography and Data Security

Cited by 105

Achieving Searchable and Privacy-Preserving Data Sharing for Cloud-Assisted E-Healthcare System

Xu, C., Wang, N., Zhu, L., Sharif, K., & Zhang, C. (2019) · IEEE Internet of Things Journal

Cryptography and Data SecurityCloud Data Security Solutions

Cited by 105

Training an Active Random Field for Real-Time Image Denoising

Barbu, A. (2009) · IEEE Transactions on Image Processing

Image and Signal Denoising MethodsImage Enhancement Techniques

Cited by 105

Cashtag Piggybacking: Uncovering Spam and Bot Activity in Stock Microblogs on Twitter

Cresci, S., Lillo, F., Regoli, D., Tardelli, S., & Tesconi, M. (2019) · ACM Transactions on the Web

Spam and Phishing DetectionMisinformation and Its Impacts

Cited by 105

An AI-Based System for Formative and Summative Assessment in Data Science Courses

Vittorini, P., Menini, S., & Tonelli, S. (2021) · International Journal of Artificial Intelligence in Education

Online Learning and AnalyticsTeaching and Learning Programming

Cited by 105

UniKGQA: Unified Retrieval and Reasoning for Solving Multi-hop Question Answering Over Knowledge Graph

Jiang, J., Zhou, K., Zhao, W. X., & Wen, J.-R. (2022) · arXiv

Topic ModelingAdvanced Graph Neural Networks

Cited by 105

Wavelet-Improved Score-Based Generative Model for Medical Imaging

Wu, W., Wang, Y., Liu, Q., Wang, G., & Zhang, J. (2024) · IEEE Transactions on Medical Imaging

Image and Signal Denoising MethodsMedical Imaging Techniques and Applications

Cited by 105

Defining a New 21st Century Skill-Computational Thinking: Concepts and Trends

Haseski, H. I., Ilic, U., & Tugtekin, U. (2018) · International Education Studies

Teaching and Learning ProgrammingEducation and Critical Thinking Development

Cited by 105

Real-Time Rotation-Invariant Face Detection with Progressive Calibration Networks

Shi, X., Shan, S., Kan, M., Wu, S., & Chen, X. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition

Face recognition and analysisAdvanced Neural Network Applications

Cited by 105

Optimal and efficient decoding of concatenated quantum block codes

Poulin, D. (2006) · Physical Review A

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 105

User gains and PD aims: assessment from a participatory design project

Bossen, C., Dindler, C., & Iversen, O. S. (2010) · Proceedings of the 11th Biennial Participatory Design Conference

Innovative Human-Technology InteractionUsability and User Interface Design

Cited by 105

The AI economist: taxation policy design via two-level deep multiagent reinforcement learning

Zheng, S., Trott, A., Srinivasa, S., Parkes, D. C., & Socher, R. (2022) · Science Advances

Reinforcement Learning in RoboticsEconomic and Fiscal Studies

Cited by 105

Context-aware rule learning from smartphone data: survey, challenges and future directions

Sarker, I. H. (2019) · Journal of Big Data

Context-Aware Activity Recognition SystemsHuman Mobility and Location-Based Analysis

Cited by 105

Adversarial attacks on an oblivious recommender

Christakopoulou, K., & Banerjee, A. (2019) · Proceedings of the 13th ACM Conference on Recommender Systems

Adversarial Robustness in Machine LearningRecommender Systems and Techniques

Cited by 105

Multimodal fusion and vision–language models: A survey for robot vision

Han, X., Chen, S., Fu, Z., Feng, Z., Fan, L., An, D., Wang, C., Guo, L., Meng, W., Zhang, X., et al. (2026) · Information Fusion

Multimodal Machine Learning ApplicationsRobot Manipulation and Learning

Cited by 105

Using Data Fusion and Web Mining to Support Feature Location in Software

Revelle, M., Dit, B., & Poshyvanyk, D. (2010) · 2010 IEEE 18th International Conference on Program Comprehension

Software Engineering ResearchSoftware Engineering Techniques and Practices

Cited by 105

NatGen: generative pre-training by “naturalizing” source code

Chakraborty, S., Ahmed, T., Ding, Y., Devanbu, P. T., & Ray, B. (2022) · Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering

Software Engineering ResearchTopic Modeling

Cited by 105

Triangular color codes on trivalent graphs with flag qubits

Chamberland, C., Kubica, A., Yoder, T. J., & Zhu, G. (2020) · New Journal of Physics

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 105

Turking in the time of COVID

Arechar, A. A., & Rand, D. G. (2021) · Behavior Research Methods

Mobile Crowdsensing and CrowdsourcingNames, Identity, and Discrimination Research

Cited by 105

End-to-end multimodal affect recognition in real-world environments

Tzirakis, P., Chen, J., Zafeiriou, S., & Schuller, B. (2021) · Information Fusion

Emotion and Mood RecognitionSentiment Analysis and Opinion Mining

Cited by 105