Check computer science papers: citations, claims and retractions

The importance of interpretability and visualization in machine learning for applications in medicine and health care

Vellido, A. (2020) · Neural Computing and Applications

Explainable Artificial Intelligence (XAI)Artificial Intelligence in Healthcare

Cited by 635

Photonic Boson Sampling in a Tunable Circuit

Broome, M. A., Fedrizzi, A., Rahimi-Keshari, S., Dove, J., Aaronson, S., Ralph, T. C., & White, A. G. (2013) · Science

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 634

QueryDet: Cascaded Sparse Query for Accelerating High-Resolution Small Object Detection

Yang, C., Huang, Z., & Wang, N. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsVisual Attention and Saliency Detection

Cited by 634

Detecting Automation of Twitter Accounts: Are You a Human, Bot, or Cyborg?

Chu, Z., Gianvecchio, S., Wang, H., & Jajodia, S. (2012) · IEEE Transactions on Dependable and Secure Computing

Spam and Phishing DetectionMisinformation and Its Impacts

Cited by 634

Visual odometry for ground vehicle applications

Nistér, D., Naroditsky, O., & Bergen, J. (2006) · Journal of Field Robotics

Robotics and Sensor-Based LocalizationAdvanced Vision and Imaging

Cited by 634

Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty

Hendrycks, D., Mazeika, M., Kadavath, S., & Song, D. (2019) · arXiv

Adversarial Robustness in Machine LearningDomain Adaptation and Few-Shot Learning

Cited by 634

P-CNN: Pose-Based CNN Features for Action Recognition

Cheron, G., Laptev, I., & Schmid, C. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV)

Human Pose and Action RecognitionHand Gesture Recognition Systems

Cited by 633

The state of the art in end-user software engineering

Ko, A. J., Abraham, R., Beckwith, L., Blackwell, A., Burnett, M., Erwig, M., Scaffidi, C., Lawrance, J., Lieberman, H., Myers, B., et al. (2011) · ACM Computing Surveys

Spreadsheets and End-User ComputingSoftware Engineering Techniques and Practices

Cited by 633

Interactive machine learning

Fails, J. A., & Olsen, D. R. (2003) · Proceedings of the 8th international conference on Intelligent user interfaces

Interactive and Immersive DisplaysUsability and User Interface Design

Cited by 633

Explainable machine learning in deployment

Bhatt, U., Xiang, A., Sharma, S., Weller, A., Taly, A., Jia, Y., Ghosh, J., Puri, R., Moura, J. M. F., & Eckersley, P. (2020) · Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 633

Learning to associate: HybridBoosted multi-target tracker for crowded scene

Li, Y., Huang, C., & Nevatia, R. (2009) · 2009 IEEE Conference on Computer Vision and Pattern Recognition

Video Surveillance and Tracking MethodsAutonomous Vehicle Technology and Safety

Cited by 633

Performance Benchmarking and Optimizing Hyperledger Fabric Blockchain Platform

Thakkar, P., Nathan, S., & Viswanathan, B. (2018) · 2018 IEEE 26th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS)

Blockchain Technology Applications and SecurityBlockchain Technology in Education and Learning

Cited by 632

Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment

Zafar, M. B., Valera, I., Gomez Rodriguez, M., & Gummadi, K. P. (2017) · Proceedings of the 26th International Conference on World Wide Web

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 632

QUANTUM WALKS AND THEIR ALGORITHMIC APPLICATIONS

AMBAINIS, A. (2003) · International Journal of Quantum Information

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 632

Unsupervised Neural Machine Translation

Artetxe, M., Labaka, G., Agirre, E., & Cho, K. (2017) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 632

Fault-tolerant quantum computation with constant error

Aharonov, D., & Ben-Or, M. (1997) · Proceedings of the twenty-ninth annual ACM symposium on Theory of computing - STOC '97

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 631

Supporting Self-Regulated Learning in Online Learning Environments and MOOCs: A Systematic Review

Wong, J., Baars, M., Davis, D., Van Der Zee, T., Houben, G.-J., & Paas, F. (2019) · International Journal of Human–Computer Interaction

Online Learning and AnalyticsInnovative Teaching and Learning Methods

Cited by 631

MedBlock: Efficient and Secure Medical Data Sharing Via Blockchain

Fan, K., Wang, S., Ren, Y., Li, H., & Yang, Y. (2018) · Journal of Medical Systems

Blockchain Technology Applications and SecurityElectronic Health Records Systems

Cited by 631

A Survey Of Methods For Explaining Black Box Models

Guidotti, R., Monreale, A., Ruggieri, S., Turini, F., Pedreschi, D., & Giannotti, F. (2018) · arXiv

Explainable Artificial Intelligence (XAI)Software Testing and Debugging Techniques

Cited by 630

Quicksilver: Fast predictive image registration – A deep learning approach

Yang, X., Kwitt, R., Styner, M., & Niethammer, M. (2017) · NeuroImage

Medical Image Segmentation TechniquesDomain Adaptation and Few-Shot Learning

Cited by 630

Probability Models for Open Set Recognition

Scheirer, W. J., Jain, L. P., & Boult, T. E. (2014) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Advanced Neural Network ApplicationsAdversarial Robustness in Machine Learning

Cited by 630

Affect and learning: An exploratory look into the role of affect in learning with AutoTutor

Craig, S., Graesser, A., Sullins, J., & Gholson, B. (2004) · Journal of Educational Media

Intelligent Tutoring Systems and Adaptive LearningInnovative Teaching and Learning Methods

Cited by 630

Issues and future directions in traffic classification

Dainotti, A., Pescape, A., & Claffy, K. (2012) · IEEE Network

Internet Traffic Analysis and Secure E-votingSoftware-Defined Networks and 5G

Cited by 630

Ego4D: Around the World in 3,000 Hours of Egocentric Video

Grauman, K., Westbury, A., Byrne, E., Chavis, Z., Furnari, A., Girdhar, R., Hamburger, J., Jiang, H., Liu, M., Liu, X., et al. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Human Pose and Action RecognitionContext-Aware Activity Recognition Systems

Cited by 630