Check computer science papers: citations, claims and retractions

Learning Latent Dynamics for Planning from Pixels

Hafner, D., Lillicrap, T., Fischer, I., Villegas, R., Ha, D., Lee, H., & Davidson, J. (2018) · arXiv

Reinforcement Learning in RoboticsAI-based Problem Solving and Planning

Cited by 708

Tactical approaches for alleviating distance in global software development

Carmel, E., & Agarwal, R. (2001) · IEEE Software

Software Engineering Techniques and PracticesTeam Dynamics and Performance

Cited by 708

A survey of symbolic execution techniques

Baldoni, R., Coppa, E., D’elia, D. C., Demetrescu, C., & Finocchi, I. (2019) · ACM Computing Surveys

Software Testing and Debugging TechniquesFormal Methods in Verification

Cited by 708

High-Speed tracking-by-detection without using image information

Bochinski, E., Eiselein, V., & Sikora, T. (2017) · 2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)

Video Surveillance and Tracking MethodsAutonomous Vehicle Technology and Safety

Cited by 707

Algorithmic injustice: A relational ethics approach

Birhane, A. (2021) · Patterns

Ethics and Social Impacts of AIFeminist Epistemology and Gender Studies

Cited by 707

Face segmentation using skin-color map in videophone applications

Chai, D., & Ngan, K. N. (1999) · IEEE Transactions on Circuits and Systems for Video Technology

Face recognition and analysisFace and Expression Recognition

Cited by 707

Artificial intelligence and illusions of understanding in scientific research

Messeri, L., & Crockett, M. J. (2024) · Nature

Ethics and Social Impacts of AIArtificial Intelligence Applications

Cited by 707

Incremental support vector learning for ordinal regression

Gu, B., Sheng, V. S., Tay, K. Y., Romano, W., & Li, S. (2015) · IEEE Transactions on Neural Networks and Learning Systems

Machine Learning and AlgorithmsMachine Learning and ELM

Cited by 707

Experimental Implementation of Fast Quantum Searching

Chuang, I. L., Gershenfeld, N., & Kubinec, M. (1998) · Physical Review Letters

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 707

NewsQA: A Machine Comprehension Dataset

Trischler, A., Wang, T., Yuan, X., Harris, J., Sordoni, A., Bachman, P., & Suleman, K. (2017) · Proceedings of the 2nd Workshop on Representation Learning for NLP

Topic ModelingNatural Language Processing Techniques

Cited by 706

Volumetry of hippocampus and amygdala with high-resolution MRI and three-dimensional analysis software: minimizing the discrepancies between laboratories

Pruessner, J. C. (2000) · Cerebral Cortex

Medical Image Segmentation TechniquesMemory and Neural Mechanisms

Cited by 706

A Comprehensive Overhaul of Feature Distillation

Heo, B., Kim, J., Yun, S., Park, H., Kwak, N., & Choi, J. Y. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 706

Search-Based Procedural Content Generation: A Taxonomy and Survey

Togelius, J., Yannakakis, G. N., Stanley, K. O., & Browne, C. (2011) · IEEE Transactions on Computational Intelligence and AI in Games

Artificial Intelligence in GamesEvolutionary Algorithms and Applications

Cited by 706

FSGAN: Subject Agnostic Face Swapping and Reenactment

Nirkin, Y., Keller, Y., & Hassner, T. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV)

Generative Adversarial Networks and Image SynthesisFace recognition and analysis

Cited by 706

A survey of appearance models in visual object tracking

Li, X., Hu, W., Shen, C., Zhang, Z., Dick, A., & Hengel, A. V. D. (2013) · ACM Transactions on Intelligent Systems and Technology

Video Surveillance and Tracking MethodsAdvanced Image and Video Retrieval Techniques

Cited by 705

Automated deep-learning system for Gleason grading of prostate cancer using biopsies: a diagnostic study

Bulten, W., Pinckaers, H., van Boven, H., Vink, R., de Bel, T., van Ginneken, B., van der Laak, J., Hulsbergen-van de Kaa, C., & Litjens, G. (2020) · The Lancet Oncology

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 705

Residual Networks Behave Like Ensembles of Relatively Shallow Networks

Veit, A., Wilber, M., & Belongie, S. (2016) · arXiv

Advanced Neural Network ApplicationsNeural Networks and Applications

Cited by 705

Cognitive Fit: An Empirical Study of Information Acquisition

Vessey, I., & Galletta, D. (1991) · Information Systems Research

Data Visualization and AnalyticsVisual and Cognitive Learning Processes

Cited by 705

Unsupervised Learning of Monocular Depth Estimation and Visual Odometry with Deep Feature Reconstruction

Zhan, H., Garg, R., Weerasekera, C. S., Li, K., Agarwal, H., & Reid, I. M. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition

Advanced Vision and ImagingRobotics and Sensor-Based Localization

Cited by 705

Spectral–Spatial Hyperspectral Image Classification With Edge-Preserving Filtering

Kang, X., Li, S., & Benediktsson, J. A. (2014) · IEEE Transactions on Geoscience and Remote Sensing

Remote-Sensing Image ClassificationAdvanced Image Fusion Techniques

Cited by 704

Bidirectional Learning for Domain Adaptation of Semantic Segmentation

Li, Y., Yuan, L., & Vasconcelos, N. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 704

Validating quantum computers using randomized model circuits

Cross, A. W., Bishop, L. S., Sheldon, S., Nation, P. D., & Gambetta, J. M. (2019) · Physical Review A

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 704

Deep Metric Learning: A Survey

KAYA, M., & BİLGE, H. Ş. (2019) · Symmetry

Face and Expression RecognitionDomain Adaptation and Few-Shot Learning

Cited by 703

PACT: Parameterized Clipping Activation for Quantized Neural Networks

Choi, J., Wang, Z., Venkataramani, S., Chuang, P. I.-J., Srinivasan, V., & Gopalakrishnan, K. (2018) · arXiv

Advanced Neural Network ApplicationsLow-power high-performance VLSI design

Cited by 703