Check computer science papers: citations, claims and retractions

Affordance, conventions, and design

Norman, D. A. (1999) · Interactions

Innovative Human-Technology InteractionUsability and User Interface Design

Cited by 2,040

Self-Supervised Visual Feature Learning With Deep Neural Networks: A Survey

Jing, L., & Tian, Y. (2021) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 2,036

A Comprehensive Survey of Graph Embedding: Problems, Techniques, and Applications

Cai, H., Zheng, V. W., & Chang, K. C.-C. (2018) · IEEE Transactions on Knowledge and Data Engineering

Advanced Graph Neural NetworksGraph Theory and Algorithms

Cited by 2,034

Advances in quantum cryptography

Pirandola, S., Andersen, U. L., Banchi, L., Berta, M., Bunandar, D., Colbeck, R., Englund, D., Gehring, T., Lupo, C., Ottaviani, C., et al. (2020) · Advances in Optics and Photonics

Quantum Information and CryptographyWireless Communication Security Techniques

Cited by 2,033

Paying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Transfer

Zagoruyko, S., & Komodakis, N. (2016) · arXiv

Advanced Neural Network ApplicationsVisual Attention and Saliency Detection

Cited by 2,027

What Is the Impact of ChatGPT on Education? A Rapid Review of the Literature

Lo, C. K. (2023) · Education Sciences

Artificial Intelligence in EducationArtificial Intelligence in Healthcare and Education

Cited by 2,024

Survey of intrusion detection systems: Techniques, datasets and challenges

Khraisat, A., Gondal, I., Vamplew, P., & Kamruzzaman, J. (2019) · Cybersecurity

Network Security and Intrusion DetectionArtificial Immune Systems Applications

Cited by 2,024

Foundations for the study of software architecture

Perry, D. E., & Wolf, A. L. (1992) · ACM SIGSOFT Software Engineering Notes

Advanced Software Engineering MethodologiesModel-Driven Software Engineering Techniques

Cited by 2,023

Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey

Akhtar, N., & Mian, A. (2018) · IEEE Access

Adversarial Robustness in Machine LearningDigital Media Forensic Detection

Cited by 2,021

Attention-Based Models for Speech Recognition

Chorowski, J., Bahdanau, D., Serdyuk, D., Cho, K., & Bengio, Y. (2015) · arXiv

Speech Recognition and SynthesisSpeech and Audio Processing

Cited by 2,021

Analysis of Representations for Domain Adaptation

Ben-David, S., Blitzer, J., Crammer, K., & Pereira, F. (2007) · Advances in Neural Information Processing Systems 19

Domain Adaptation and Few-Shot LearningMachine Learning and Algorithms

Cited by 2,019

Exploring the impact of artificial intelligence on teaching and learning in higher education

Popenici, S. A. D., & Kerr, S. (2017) · Research and Practice in Technology Enhanced Learning

Artificial Intelligence in EducationArtificial Intelligence in Healthcare and Education

Cited by 2,019

Resistance to Medical Artificial Intelligence

Longoni, C., Bonezzi, A., & Morewedge, C. K. (2019) · Journal of Consumer Research

AI in Service InteractionsArtificial Intelligence in Healthcare and Education

Cited by 2,015

Attention gated networks: learning to leverage salient regions in medical images

Schlemper, J., Oktay, O., Schaap, M., Heinrich, M., Kainz, B., Glocker, B., & Rueckert, D. (2019) · Medical Image Analysis

Medical Image Segmentation TechniquesAdvanced Neural Network Applications

Cited by 2,014

Deep learning for sensor-based activity recognition: A survey

Wang, J., Chen, Y., Hao, S., Peng, X., & Hu, L. (2019) · Pattern Recognition Letters

Context-Aware Activity Recognition SystemsGait Recognition and Analysis

Cited by 2,014

Large language models are zero-shot reasoners

Kojima, T., Gu, S. (., Reid, M., Matsuo, Y., & Iwasawa, Y. (2022) · Advances in Neural Information Processing Systems 35

Topic ModelingNatural Language Processing Techniques

Cited by 2,013

Large Language Models are Zero-Shot Reasoners

Kojima, T., Gu, S. S., Reid, M., Matsuo, Y., & Iwasawa, Y. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 2,013

Artificial intelligence in higher education: the state of the field

Crompton, H., & Burke, D. (2023) · International Journal of Educational Technology in Higher Education

Artificial Intelligence in EducationIntelligent Tutoring Systems and Adaptive Learning

Cited by 2,010

Second-Order Attention Network for Single Image Super-Resolution

Dai, T., Cai, J., Zhang, Y., Xia, S.-T., & Zhang, L. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Image Processing TechniquesAdvanced Neural Network Applications

Cited by 2,010

An efficient solution to the five-point relative pose problem

Nister, D. (2004) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Advanced Vision and ImagingRobotics and Sensor-Based Localization

Cited by 2,009

Motion Planning in Dynamic Environments Using Velocity Obstacles

Fiorini, P., & Shiller, Z. (1998) · The International Journal of Robotics Research

Robotic Path Planning AlgorithmsReinforcement Learning in Robotics

Cited by 2,008

Robust object tracking with online multiple instance learning

Babenko, B., Yang, M.-H., & Belongie, S. (2011) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Video Surveillance and Tracking MethodsAdvanced Neural Network Applications

Cited by 2,007

YOLOv8: A Novel Object Detection Algorithm with Enhanced Performance and Robustness

Varghese, R., & M., S. (2024) · 2024 International Conference on Advances in Data Engineering and Intelligent Computing Systems (ADICS)

Advanced Neural Network ApplicationsVisual Attention and Saliency Detection

Cited by 2,007

Return of Frustratingly Easy Domain Adaptation

Sun, B., Feng, J., & Saenko, K. (2016) · Proceedings of the AAAI Conference on Artificial Intelligence

Domain Adaptation and Few-Shot LearningReinforcement Learning in Robotics

Cited by 2,004