Check computer science papers: citations, claims and retractions

Eye guidance in natural vision: reinterpreting salience

Tatler, B. W., Hayhoe, M. M., Land, M. F., & Ballard, D. H. (2011) · Journal of Vision

Visual Attention and Saliency DetectionVisual perception and processing mechanisms

Cited by 775

Use of relative code churn measures to predict system defect density

Nagappan, N., & Ball, T. (2005) · Proceedings of the 27th international conference on Software engineering - ICSE '05

Software Engineering ResearchSoftware Reliability and Analysis Research

Cited by 775

The Promise of the Maker Movement for Education

Martin, L. (2015) · Journal of Pre-College Engineering Education Research (J-PEER)

Teaching and Learning ProgrammingDesign Education and Practice

Cited by 775

Unsupervised Learning of Depth and Ego-Motion from Monocular Video Using 3D Geometric Constraints

Mahjourian, R., Wicke, M., & Angelova, A. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition

Advanced Vision and ImagingRobotics and Sensor-Based Localization

Cited by 775

Multi-Classification of Brain Tumor Images Using Deep Neural Network

Sultan, H. H., Salem, N. M., & Al-Atabany, W. (2019) · IEEE Access

Brain Tumor Detection and ClassificationGlioma Diagnosis and Treatment

Cited by 775

Empowering things with intelligence: a survey of the progress, challenges, and opportunities in artificial intelligence of things

Zhang, J., & Tao, D. (2021) · IEEE Internet of Things Journal

IoT and Edge/Fog ComputingInternet of Things and AI

Cited by 774

A Survey on Federated Learning for Resource-Constrained IoT Devices

Imteaj, A., Thakker, U., Wang, S., Li, J., & Amini, M. H. (2022) · IEEE Internet of Things Journal

Privacy-Preserving Technologies in DataIoT and Edge/Fog Computing

Cited by 774

A new learning paradigm: Learning using privileged information

Vapnik, V., & Vashist, A. (2009) · Neural Networks

Machine Learning and AlgorithmsMachine Learning and Data Classification

Cited by 774

Analysis of k-Fold Cross-Validation over Hold-Out Validation on Colossal Datasets for Quality Classification

Yadav, S., & Shukla, S. (2016) · 2016 IEEE 6th International Conference on Advanced Computing (IACC)

Machine Learning and Data ClassificationData Mining and Machine Learning Applications

Cited by 773

Spotting fake reviewer groups in consumer reviews

Mukherjee, A., Liu, B., & Glance, N. (2012) · Proceedings of the 21st international conference on World Wide Web

Spam and Phishing DetectionMisinformation and Its Impacts

Cited by 773

What makes for good views for contrastive learning

Tian, Y., Sun, C., Poole, B., Krishnan, D., Schmid, C., & Isola, P. (2020) · arXiv

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 773

Noise-induced barren plateaus in variational quantum algorithms

Wang, S., Fontana, E., Cerezo, M., Sharma, K., Sone, A., Cincio, L., & Coles, P. J. (2021) · Nature Communications

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 773

Automated cardiovascular magnetic resonance image analysis with fully convolutional networks

Bai, W., Sinclair, M., Tarroni, G., Oktay, O., Rajchl, M., Vaillant, G., Lee, A. M., Aung, N., Lukaschuk, E., Sanghvi, M. M., et al. (2018) · Journal of Cardiovascular Magnetic Resonance

Medical Image Segmentation TechniquesCardiac Imaging and Diagnostics

Cited by 773

Suppressing Uncertainties for Large-Scale Facial Expression Recognition

Wang, K., Peng, X., Yang, J., Lu, S., & Qiao, Y. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Emotion and Mood RecognitionFace recognition and analysis

Cited by 772

Realistic Evaluation of Deep Semi-Supervised Learning Algorithms

Oliver, A., Odena, A., Raffel, C., Cubuk, E. D., & Goodfellow, I. J. (2018) · arXiv

Machine Learning and AlgorithmsDomain Adaptation and Few-Shot Learning

Cited by 772

From the Quantum Approximate Optimization Algorithm to a Quantum Alternating Operator Ansatz

Hadfield, S., Wang, Z., O’Gorman, B., Rieffel, E. G., Venturelli, D., & Biswas, R. (2019) · Algorithms

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 772

Data association in stochastic mapping using the joint compatibility test

Neira, J., & Tardos, J. D. (2001) · IEEE Transactions on Robotics and Automation

Robotics and Sensor-Based LocalizationTarget Tracking and Data Fusion in Sensor Networks

Cited by 772

Latent retrieval for weakly supervised open domain question answering

Lee, K., Chang, M.-W., & Toutanova, K. (2019) · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics

Topic ModelingInformation Retrieval and Search Behavior

Cited by 771

Learning Stable Nonlinear Dynamical Systems With Gaussian Mixture Models

Khansari-Zadeh, S. M., & Billard, A. (2011) · IEEE Transactions on Robotics

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 771

Domain Generalization via Invariant Feature Representation

Muandet, K., Balduzzi, D., & Schölkopf, B. (2013) · arXiv

Domain Adaptation and Few-Shot LearningMachine Learning and Algorithms

Cited by 771

Introducing the RECOLA multimodal corpus of remote collaborative and affective interactions

Ringeval, F., Sonderegger, A., Sauer, J., & Lalanne, D. (2013) · 2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG)

Emotion and Mood RecognitionSpeech and dialogue systems

Cited by 771

Structured information extraction from scientific text with large language models

Dagdelen, J., Dunn, A., Lee, S., Walker, N., Rosen, A. S., Ceder, G., Persson, K. A., & Jain, A. (2024) · Nature Communications

Topic ModelingMachine Learning in Materials Science

Cited by 771

The Factor Structure of the Presence Questionnaire

Witmer, B. G., Jerome, C. J., & Singer, M. J. (2005) · Presence: Teleoperators and Virtual Environments

Virtual Reality Applications and ImpactsFlow Experience in Various Fields

Cited by 770

Kimi K2.5: Visual Agentic Intelligence

Kimi Team, Bai, T., Bai, Y., Bao, Y., Cai, S. H., Cao, Y., Chai, Z., Charles, Y., Che, H. S., Chen, C., et al. (2026) · arXiv

Multimodal Machine Learning ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 770