Most cited computer science papers
- Verified
Capture versus suppression of attention by salient singletons: Electrophysiological evidence for an automatic attend-to-me signal
Sawaki, R., & Luck, S. J. (2010) · Attention, Perception, & Psychophysics
Visual Attention and Saliency DetectionVisual perception and processing mechanisms
Cited by 487
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NAS-Unet: Neural Architecture Search for Medical Image Segmentation
Weng, Y., Zhou, T., Li, Y., & Qiu, X. (2019) · IEEE Access
Medical Image Segmentation TechniquesAdvanced Neural Network Applications
Cited by 487
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Leases: an efficient fault-tolerant mechanism for distributed file cache consistency
Gray, C., & Cheriton, D. (1989) · Proceedings of the twelfth ACM symposium on Operating systems principles
Distributed systems and fault toleranceAdvanced Data Storage Technologies
Cited by 487
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Visualizing Deep Neural Network Decisions: Prediction Difference Analysis
Zintgraf, L. M., Cohen, T. S., Adel, T., & Welling, M. (2017) · arXiv
Explainable Artificial Intelligence (XAI)Advanced Neural Network Applications
Cited by 487
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Massive Exploration of Neural Machine Translation Architectures
Britz, D., Goldie, A., Luong, M.-T., & Le, Q. (2017) · arXiv
Natural Language Processing TechniquesTopic Modeling
Cited by 487
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MMBench: Is Your Multi-modal Model an All-around Player?
Liu, Y., Duan, H., Zhang, Y., Li, B., Zhang, S., Zhao, W., Yuan, Y., Wang, J., He, C., Liu, Z., et al. (2023) · arXiv
Multimodal Machine Learning ApplicationsAdvanced Neural Network Applications
Cited by 487
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Mining e-mail content for author identification forensics
de Vel, O., Anderson, A., Corney, M., & Mohay, G. (2001) · ACM SIGMOD Record
Authorship Attribution and ProfilingText and Document Classification Technologies
Cited by 487
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Using an LLM to Help With Code Understanding
Nam, D., Macvean, A., Hellendoorn, V., Vasilescu, B., & Myers, B. (2024) · Proceedings of the IEEE/ACM 46th International Conference on Software Engineering
Software Engineering ResearchSoftware Engineering Techniques and Practices
Cited by 487
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A noise-based IC random number generator for applications in cryptography
Petrie, C. S., & Connelly, J. A. (2000) · IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications
Physical Unclonable Functions (PUFs) and Hardware SecurityAnalog and Mixed-Signal Circuit Design
Cited by 487
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Artificial Intelligence in Society
OECD (2019) · OECD eBooks
Ethics and Social Impacts of AIDigitalization, Law, and Regulation
Cited by 487
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VoxelNeXt: Fully Sparse VoxelNet for 3D Object Detection and Tracking
Chen, Y., Liu, J., Zhang, X., Qi, X., & Jia, J. (2023) · arXiv
Advanced Neural Network ApplicationsAutonomous Vehicle Technology and Safety
Cited by 486
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Shift: a technique for operating pen- based interfaces using touch
Vogel, D., & Baudisch, P. (2007) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Interactive and Immersive DisplaysUsability and User Interface Design
Cited by 486
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Public perception of the COVID-19 pandemic on Twitter: Sentiment analysis and topic modeling study
Boon-Itt, S., & Skunkan, Y. (2020) · JMIR Public Health and Surveillance
Sentiment Analysis and Opinion MiningCommunication and COVID-19 Impact
Cited by 486
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Evolutionary algorithms: A critical review and its future prospects
Vikhar, P. A. (2016) · 2016 International Conference on Global Trends in Signal Processing, Information Computing and Communication (ICGTSPICC)
Metaheuristic Optimization Algorithms ResearchEvolutionary Algorithms and Applications
Cited by 486
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Health monitoring in the home of the future
Korhonen, I., Parkka, J., & Van Gils, M. (2003) · IEEE Engineering in Medicine and Biology Magazine
Context-Aware Activity Recognition SystemsNon-Invasive Vital Sign Monitoring
Cited by 486
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Mobile fog: a programming model for large-scale applications on the internet of things
Hong, K., Lillethun, D., Ramachandran, U., Ottenwälder, B., & Koldehofe, B. (2013) · Proceedings of the second ACM SIGCOMM workshop on Mobile cloud computing
IoT and Edge/Fog ComputingDistributed and Parallel Computing Systems
Cited by 486
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Operator quantum error-correcting subsystems for self-correcting quantum memories
Bacon, D. (2006) · Physical Review A
Quantum Computing Algorithms and ArchitectureQuantum many-body systems
Cited by 486
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On Adaptive Attacks to Adversarial Example Defenses
Tramer, F., Carlini, N., Brendel, W., & Madry, A. (2020) · arXiv
Adversarial Robustness in Machine LearningSecurity and Verification in Computing
Cited by 486
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Realization of a scalable Shor algorithm
Monz, T., Nigg, D., Martinez, E. A., Brandl, M. F., Schindler, P., Rines, R., Wang, S. X., Chuang, I. L., & Blatt, R. (2016) · Science
Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography
Cited by 486
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High-threshold universal quantum computation on the surface code
Fowler, A. G., Stephens, A. M., & Groszkowski, P. (2009) · Physical Review A
Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography
Cited by 486
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Machine learning and neurosurgical outcome prediction: a systematic review
Senders, J. T., Staples, P. C., Karhade, A. V., Zaki, M. M., Gormley, W. B., Broekman, M. L. D., Smith, T. R., & Arnaout, O. (2018) · World Neurosurgery
Machine Learning in HealthcareArtificial Intelligence in Healthcare
Cited by 486
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Internet traffic classification demystified: myths, caveats, and the best practices
Kim, H., Claffy, K., Fomenkov, M., Barman, D., Faloutsos, M., & Lee, K. (2008) · Proceedings of the 2008 ACM CoNEXT Conference on - CONEXT '08
Internet Traffic Analysis and Secure E-votingNetwork Traffic and Congestion Control
Cited by 485
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Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation
Gao, D., Wang, H., Li, Y., Sun, X., Qian, Y., Ding, B., & Zhou, J. (2023) · arXiv
Topic ModelingNatural Language Processing Techniques
Cited by 485
- Verified
Test Collection Based Evaluation of Information Retrieval Systems
Sanderson, M. (2010) · Foundations and Trends® in Information Retrieval
Information Retrieval and Search BehaviorRecommender Systems and Techniques
Cited by 485
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