Check computer science papers: citations, claims and retractions

A survey of advanced techniques for spectrum sharing in 5G networks

Zhang, L., Xiao, M., Wu, G., Alam, M., Liang, Y.-C., & Li, S. (2017) · IEEE Wireless Communications

Cognitive Radio Networks and Spectrum SensingAdvanced MIMO Systems Optimization

Cited by 321

The synthesis and rendering of eroded fractal terrains

Musgrave, F. K., Kolb, C. E., & Mace, R. S. (1989) · Proceedings of the 16th annual conference on Computer graphics and interactive techniques

Computer Graphics and Visualization Techniques3D Shape Modeling and Analysis

Cited by 321

ChatGPT: Applications, Opportunities, and Threats

Bahrini, A., Khamoshifar, M., Abbasimehr, H., Riggs, R. J., Esmaeili, M., Majdabadkohne, R. M., & Pasehvar, M. (2023) · 2023 Systems and Information Engineering Design Symposium (SIEDS)

Artificial Intelligence ApplicationsTopic Modeling

Cited by 321

Machine Learning for Healthcare Wearable Devices: The Big Picture

Sabry, F., Eltaras, T., Labda, W., Alzoubi, K., & Malluhi, Q. (2022) · Journal of Healthcare Engineering

Context-Aware Activity Recognition SystemsNon-Invasive Vital Sign Monitoring

Cited by 321

Realization of an Error-Correcting Surface Code with Superconducting Qubits

Zhao, Y., Ye, Y., Huang, H.-L., Zhang, Y., Wu, D., Guan, H., Zhu, Q., Wei, Z., He, T., Cao, S., et al. (2022) · Physical Review Letters

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 321

A Comparative Analysis of LiDAR SLAM-Based Indoor Navigation for Autonomous Vehicles

Zou, Q., Sun, Q., Chen, L., Nie, B., & Li, Q. (2022) · IEEE Transactions on Intelligent Transportation Systems

Robotics and Sensor-Based Localization3D Surveying and Cultural Heritage

Cited by 321

A Review on the Application of Blockchain to the Next Generation of Cybersecure Industry 4.0 Smart Factories

Fernandez-Carames, T. M., & Fraga-Lamas, P. (2019) · IEEE Access

Blockchain Technology Applications and SecurityDigital Transformation in Industry

Cited by 321

SACNN: Self-Attention Convolutional Neural Network for Low-Dose CT Denoising With Self-Supervised Perceptual Loss Network

Li, M., Hsu, W., Xie, X., Cong, J., & Gao, W. (2020) · IEEE Transactions on Medical Imaging

Image and Signal Denoising MethodsImage Enhancement Techniques

Cited by 321

Bias recognition and mitigation strategies in artificial intelligence healthcare applications

Hasanzadeh, F., Josephson, C. B., Waters, G., Adedinsewo, D., Azizi, Z., & White, J. A. (2025) · npj Digital Medicine

Ethics and Social Impacts of AIArtificial Intelligence in Healthcare and Education

Cited by 320

Are Explanations Helpful? A Comparative Study of the Effects of Explanations in AI-Assisted Decision-Making

Wang, X., & Yin, M. (2021) · 26th International Conference on Intelligent User Interfaces

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

Cited by 320

Learning with Augmented Features for Heterogeneous Domain Adaptation

Duan, L., Xu, D., & Tsang, I. (2012) · arXiv

Domain Adaptation and Few-Shot LearningMachine Learning and Algorithms

Cited by 320

Treatment of acrophobia in virtual reality: The role of immersion and presence

Krijn, M., Emmelkamp, P. M. G., Biemond, R., de Wilde de Ligny, C., Schuemie, M. J., & van der Mast, C. A. P. G. (2004) · Behaviour Research and Therapy

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

Cited by 320

StatLog: Comparison of classification algorithms on large real-world problems

KING, R. D., FENG, C., & SUTHERLAND, A. (1995) · Applied Artificial Intelligence

Data Mining and Machine Learning ApplicationsMachine Learning and Data Classification

Cited by 320

Leaky Cauldron on the Dark Land: Understanding Memory Side-Channel Hazards in SGX

Wang, W., Chen, G., Pan, X., Zhang, Y., Wang, X., Bindschaedler, V., Tang, H., & Gunter, C. A. (2017) · Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security

Security and Verification in ComputingCryptographic Implementations and Security

Cited by 320

Big Data’s End Run around Anonymity and Consent

Barocas, S., & Nissenbaum, H. (2014) · Privacy, Big Data, and the Public Good

Ethics and Social Impacts of AIPrivacy, Security, and Data Protection

Cited by 320

Exploring Temporal Coherence for More General Video Face Forgery Detection

Zheng, Y., Bao, J., Chen, D., Zeng, M., & Wen, F. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Digital Media Forensic DetectionGenerative Adversarial Networks and Image Synthesis

Cited by 320

Dynamic Multi-Scale Filters for Semantic Segmentation

He, J., Deng, Z., & Qiao, Y. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 320

Data Uncertainty Learning in Face Recognition

Chang, J., Lan, Z., Cheng, C., & Wei, Y. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Face recognition and analysisFace and Expression Recognition

Cited by 320

Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debate

Liang, T., He, Z., Jiao, W., Wang, X., Wang, Y., Wang, R., Yang, Y., Shi, S., & Tu, Z. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 320

Blockchain-based solutions to security and privacy issues in the internet of things

Yu, Y., Li, Y., Tian, J., & Liu, J. (2018) · IEEE Wireless Communications

Blockchain Technology Applications and SecurityIoT and Edge/Fog Computing

Cited by 320

Deep convolutional neural network and 3D deformable approach for tissue segmentation in musculoskeletal magnetic resonance imaging

Liu, F., Zhou, Z., Jang, H., Samsonov, A., Zhao, G., & Kijowski, R. (2018) · Magnetic Resonance in Medicine

Medical Image Segmentation TechniquesMedical Imaging and Analysis

Cited by 319

Neural Optimizer Search with Reinforcement Learning

Bello, I., Zoph, B., Vasudevan, V., & Le, Q. V. (2017) · arXiv

Stochastic Gradient Optimization TechniquesMachine Learning and Data Classification

Cited by 319

Emotions Don't Lie: An Audio-Visual Deepfake Detection Method using Affective Cues

Mittal, T., Bhattacharya, U., Chandra, R., Bera, A., & Manocha, D. (2020) · Proceedings of the 28th ACM International Conference on Multimedia

Digital Media Forensic DetectionMisinformation and Its Impacts

Cited by 319

Facial emotion recognition using multi-modal information

De Silva, L. C., Miyasato, T., & Nakatsu, R. (2002) · Proceedings of ICICS, 1997 International Conference on Information, Communications and Signal Processing. Theme: Trends in Information Systems Engineering and Wireless Multimedia Communications (Cat. No.97TH8237)

Emotion and Mood RecognitionSpeech and Audio Processing

Cited by 319