Most cited computer science papers
- Verified
Routledge International Handbook of Participatory Design
Simonsen, J. (2012) · Routledge eBooks
Innovative Human-Technology InteractionUsability and User Interface Design
Cited by 1,606
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A Survey on Performance Metrics for Object-Detection Algorithms
Padilla, R., Netto, S. L., & da Silva, E. A. B. (2020) · 2020 International Conference on Systems, Signals and Image Processing (IWSSIP)
Advanced Neural Network ApplicationsVisual Attention and Saliency Detection
Cited by 1,605
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Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks
Bousmalis, K., Silberman, N., Dohan, D., Erhan, D., & Krishnan, D. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Domain Adaptation and Few-Shot LearningGenerative Adversarial Networks and Image Synthesis
Cited by 1,603
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Learning under Concept Drift: A Review
Lu, J., Liu, A., Dong, F., Gu, F., Gama, J., & Zhang, G. (2018) · IEEE Transactions on Knowledge and Data Engineering
Data Stream Mining TechniquesDomain Adaptation and Few-Shot Learning
Cited by 1,603
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The classical-quantum boundary for correlations: Discord and related measures
Modi, K., Brodutch, A., Cable, H., Paterek, T., & Vedral, V. (2012) · Reviews of Modern Physics
Quantum Information and CryptographyQuantum Mechanics and Applications
Cited by 1,600
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Lost in the Middle: How Language Models Use Long Contexts
Liu, N. F., Lin, K., Hewitt, J., Paranjape, A., Bevilacqua, M., Petroni, F., & Liang, P. (2023) · arXiv
Topic ModelingNatural Language Processing Techniques
Cited by 1,599
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Reconciling modern machine-learning practice and the classical bias–variance trade-off
Belkin, M., Hsu, D., Ma, S., & Mandal, S. (2019) · Proceedings of the National Academy of Sciences
Stochastic Gradient Optimization TechniquesMachine Learning and Algorithms
Cited by 1,595
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Theory of quantum error-correcting codes
Knill, E., & Laflamme, R. (1997) · Physical Review A
Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography
Cited by 1,593
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ATOM: Accurate Tracking by Overlap Maximization
Danelljan, M., Bhat, G., Khan, F. S., & Felsberg, M. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Video Surveillance and Tracking MethodsAdvanced Neural Network Applications
Cited by 1,591
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Heterogeneous Graph Neural Network
Zhang, C., Song, D., Huang, C., Swami, A., & Chawla, N. V. (2019) · Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
Advanced Graph Neural NetworksRecommender Systems and Techniques
Cited by 1,591
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Memory Aware Synapses: Learning What (not) to Forget
Aljundi, R., Babiloni, F., Elhoseiny, M., Rohrbach, M., & Tuytelaars, T. (2018) · Lecture Notes in Computer Science
Domain Adaptation and Few-Shot LearningNeural Networks and Applications
Cited by 1,590
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Architecture for a large-scale ion-trap quantum computer
Kielpinski, D., Monroe, C., & Wineland, D. J. (2002) · Nature
Quantum Information and CryptographyQuantum Computing Algorithms and Architecture
Cited by 1,589
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Transformer Tracking
Chen, X., Yan, B., Zhu, J., Wang, D., Yang, X., & Lu, H. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Video Surveillance and Tracking MethodsAdvanced Neural Network Applications
Cited by 1,588
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Deformable medical image registration: a survey
Sotiras, A., Davatzikos, C., & Paragios, N. (2013) · IEEE Transactions on Medical Imaging
Medical Image Segmentation TechniquesAdvanced Radiotherapy Techniques
Cited by 1,587
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Hybrid Task Cascade for Instance Segmentation
Chen, K., Pang, J., Wang, J., Xiong, Y., Li, X., Sun, S., Feng, W., Liu, Z., Shi, J., Ouyang, W., et al. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Advanced Neural Network ApplicationsVisual Attention and Saliency Detection
Cited by 1,587
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Cross-lingual Language Model Pretraining
Lample, G., & Conneau, A. (2019) · arXiv
Topic ModelingNatural Language Processing Techniques
Cited by 1,586
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Bag of Tricks and a Strong Baseline for Deep Person Re-Identification
Luo, H., Gu, Y., Liao, X., Lai, S., & Jiang, W. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Video Surveillance and Tracking MethodsAdvanced Neural Network Applications
Cited by 1,584
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Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual Grounding
Fukui, A., Park, D. H., Yang, D., Rohrbach, A., Darrell, T., & Rohrbach, M. (2016) · Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing
Multimodal Machine Learning ApplicationsAdvanced Image and Video Retrieval Techniques
Cited by 1,582
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AntNet: Distributed Stigmergetic Control for Communications Networks
Di Caro, G., & Dorigo, M. (1998) · Journal of Artificial Intelligence Research
Metaheuristic Optimization Algorithms ResearchNetwork Traffic and Congestion Control
Cited by 1,579
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Mamba: Linear-Time Sequence Modeling with Selective State Spaces
Gu, A., & Dao, T. (2023) · arXiv
Topic ModelingAdvanced Neural Network Applications
Cited by 1,579
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Adversarial Autoencoders
Makhzani, A., Shlens, J., Jaitly, N., Goodfellow, I., & Frey, B. (2015) · arXiv
Generative Adversarial Networks and Image SynthesisAdversarial Robustness in Machine Learning
Cited by 1,579
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A comprehensive AI policy education framework for university teaching and learning
Chan, C. K. Y. (2023) · International Journal of Educational Technology in Higher Education
Artificial Intelligence in EducationArtificial Intelligence in Healthcare and Education
Cited by 1,577
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On the Convergence of FedAvg on Non-IID Data
Li, X., Huang, K., Yang, W., Wang, S., & Zhang, Z. (2019) · arXiv
Privacy-Preserving Technologies in DataStochastic Gradient Optimization Techniques
Cited by 1,575
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Understanding the Effective Receptive Field in Deep Convolutional Neural Networks
Luo, W., Li, Y., Urtasun, R., & Zemel, R. (2017) · arXiv
Advanced Neural Network ApplicationsVisual Attention and Saliency Detection
Cited by 1,575
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