Most cited computer science papers
- Verified
Learning to Prompt for Vision-Language Models
Zhou, K., Yang, J., Loy, C. C., & Liu, Z. (2022) · International Journal of Computer Vision
Domain Adaptation and Few-Shot LearningMultimodal Machine Learning Applications
Cited by 3,304
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Python for scientific computing
Oliphant, T. E. (2007) · Computing in Science & Engineering
Computational Physics and Python ApplicationsParallel Computing and Optimization Techniques
Cited by 3,303
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Lexicon-based methods for sentiment analysis
Taboada, M., Brooke, J., Tofiloski, M., Voll, K., & Stede, M. (2011) · Computational Linguistics
Sentiment Analysis and Opinion MiningEmotion and Mood Recognition
Cited by 3,301
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Dueling Network Architectures for Deep Reinforcement Learning
Wang, Z., Schaul, T., Hessel, M., van Hasselt, H., Lanctot, M., & de Freitas, N. (2015) · arXiv
Reinforcement Learning in RoboticsArtificial Intelligence in Games
Cited by 3,300
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The class imbalance problem: A systematic study1
Japkowicz, N., & Stephen, S. (2002) · Intelligent Data Analysis
Imbalanced Data Classification TechniquesMachine Learning and Data Classification
Cited by 3,295
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Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer
Ehteshami Bejnordi, B., Veta, M., Johannes van Diest, P., van Ginneken, B., Karssemeijer, N., Litjens, G., van der Laak, J. A. W. M., and the CAMELYON16 Consortium, Hermsen, M., Manson, Q. F., et al. (2017) · JAMA
AI in cancer detectionRadiomics and Machine Learning in Medical Imaging
Cited by 3,293
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Temporal Fusion Transformers for interpretable multi-horizon time series forecasting
Lim, B., Arık, S. Ö., Loeff, N., & Pfister, T. (2021) · International Journal of Forecasting
Time Series Analysis and ForecastingForecasting Techniques and Applications
Cited by 3,291
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International evaluation of an AI system for breast cancer screening
McKinney, S. M., Sieniek, M., Godbole, V., Godwin, J., Antropova, N., Ashrafian, H., Back, T., Chesus, M., Corrado, G. S., Darzi, A., et al. (2020) · Nature
AI in cancer detectionDigital Radiography and Breast Imaging
Cited by 3,287
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RefineNet: Multi-path Refinement Networks for High-Resolution Semantic Segmentation
Lin, G., Milan, A., Shen, C., & Reid, I. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning
Cited by 3,287
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The knowledge complexity of interactive proof systems
Goldwasser, S., Micali, S., & Rackoff, C. (1989) · SIAM Journal on Computing
Cryptography and Data SecurityComplexity and Algorithms in Graphs
Cited by 3,285
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SUN database: Large-scale scene recognition from abbey to zoo
Xiao, J., Hays, J., Ehinger, K. A., Oliva, A., & Torralba, A. (2010) · 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Advanced Image and Video Retrieval TechniquesAdvanced Neural Network Applications
Cited by 3,283
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A theory of the learnable
Valiant, L. G. (1984) · Communications of the ACM
Machine Learning and AlgorithmsComputability, Logic, AI Algorithms
Cited by 3,279
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Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?
Tajbakhsh, N., Shin, J. Y., Gurudu, S. R., Hurst, R. T., Kendall, C. B., Gotway, M. B., & Liang, J. (2016) · IEEE Transactions on Medical Imaging
Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications
Cited by 3,277
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Unsupervised Monocular Depth Estimation with Left-Right Consistency
Godard, C., Aodha, O. M., & Brostow, G. J. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Advanced Vision and ImagingAdvanced Neural Network Applications
Cited by 3,270
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Quantum information and computation
Bennett, C. H., & DiVincenzo, D. P. (2000) · Nature
Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography
Cited by 3,263
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Mobile Edge Computing: A Survey on Architecture and Computation Offloading
Mach, P., & Becvar, Z. (2017) · IEEE Communications Surveys & Tutorials
IoT and Edge/Fog ComputingCaching and Content Delivery
Cited by 3,258
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Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images
Nguyen, A., Yosinski, J., & Clune, J. (2014) · arXiv
Adversarial Robustness in Machine LearningDigital Media Forensic Detection
Cited by 3,258
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Region Filling and Object Removal by Exemplar-Based Image Inpainting
Criminisi, A., Perez, P., & Toyama, K. (2004) · IEEE Transactions on Image Processing
Generative Adversarial Networks and Image SynthesisImage and Signal Denoising Methods
Cited by 3,258
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Deep neural networks are easily fooled: High confidence predictions for unrecognizable images
Nguyen, A., Yosinski, J., & Clune, J. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Adversarial Robustness in Machine LearningDigital Media Forensic Detection
Cited by 3,258
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Randomized Kinodynamic Planning
LaValle, S. M., & Kuffner, J. J. (2001) · The International Journal of Robotics Research
Robotic Path Planning AlgorithmsReinforcement Learning in Robotics
Cited by 3,254
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PCA versus LDA
Martinez, A. M., & Kak, A. C. (2001) · IEEE Transactions on Pattern Analysis and Machine Intelligence
Face and Expression RecognitionStatistical Methods and Applications
Cited by 3,249
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PubChem 2019 update: improved access to chemical data
Kim, S., Chen, J., Cheng, T., Gindulyte, A., He, J., He, S., Li, Q., Shoemaker, B. A., Thiessen, P. A., Yu, B., et al. (2019) · Nucleic Acids Research
Computational Drug Discovery MethodsBiomedical Text Mining and Ontologies
Cited by 3,249
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DARTS: Differentiable architecture search
Liu, H., Simonyan, K., & Yang, Y. (2018) · arXiv
Advanced Neural Network ApplicationsMachine Learning and Data Classification
Cited by 3,248
- Verified
Eyeriss: An Energy-Efficient Reconfigurable Accelerator for Deep Convolutional Neural Networks
Chen, Y.-H., Krishna, T., Emer, J. S., & Sze, V. (2017) · IEEE Journal of Solid-State Circuits
Advanced Neural Network ApplicationsParallel Computing and Optimization Techniques
Cited by 3,247
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