Check computer science papers: citations, claims and retractions

A decade of social bot detection

Cresci, S. (2020) · Communications of the ACM

Spam and Phishing DetectionMisinformation and Its Impacts

Cited by 323

Usability ratings for everyday products measured with the System Usability Scale

Kortum, P. T., & Bangor, A. (2013) · International Journal of Human-Computer Interaction

Usability and User Interface DesignInnovative Human-Technology Interaction

Cited by 323

Survey on Fully Homomorphic Encryption, Theory, and Applications

Marcolla, C., Sucasas, V., Manzano, M., Bassoli, R., Fitzek, F. H. P., & Aaraj, N. (2022) · Proceedings of the IEEE

Cryptography and Data SecurityCloud Data Security Solutions

Cited by 323

Reduced-Reference Image Quality Assessment Using Divisive Normalization-Based Image Representation

Li, Q., & Wang, Z. (2009) · IEEE Journal of Selected Topics in Signal Processing

Image and Video Quality AssessmentImage Retrieval and Classification Techniques

Cited by 323

Interleaved Group Convolutions

Zhang, T., Qi, G.-J., Xiao, B., & Wang, J. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 323

AutoFormer: Searching Transformers for Visual Recognition

Chen, M., Peng, H., Fu, J., & Ling, H. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 323

Learning Factorized Multimodal Representations

Tsai, Y.-H. H., Liang, P. P., Zadeh, A., Morency, L.-P., & Salakhutdinov, R. (2018) · arXiv

Multimodal Machine Learning ApplicationsSentiment Analysis and Opinion Mining

Cited by 323

Convergence of Blockchain and Edge Computing for Secure and Scalable IIoT Critical Infrastructures in Industry 4.0

Wu, Y., Dai, H.-N., & Wang, H. (2021) · IEEE Internet of Things Journal

Blockchain Technology Applications and SecurityIoT and Edge/Fog Computing

Cited by 323

Adiabatic quantum state generation and statistical zero knowledge

Aharonov, D., & Ta-Shma, A. (2003) · Proceedings of the thirty-fifth annual ACM symposium on Theory of computing

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 322

Perceptual quality prediction on authentically distorted images using a bag of features approach

Ghadiyaram, D., & Bovik, A. C. (2017) · Journal of Vision

Image and Video Quality AssessmentImage Retrieval and Classification Techniques

Cited by 322

InterpretML: A Unified Framework for Machine Learning Interpretability

Nori, H., Jenkins, S., Koch, P., & Caruana, R. (2019) · arXiv

Explainable Artificial Intelligence (XAI)Software Testing and Debugging Techniques

Cited by 322

Consistent video depth estimation

Luo, X., Huang, J.-B., Szeliski, R., Matzen, K., & Kopf, J. (2020) · ACM Transactions on Graphics

Advanced Vision and Imaging3D Shape Modeling and Analysis

Cited by 322

The analytical solution of the additive constant problem

Cailliez, F. (1983) · Psychometrika

Matrix Theory and AlgorithmsPsychometric Methodologies and Testing

Cited by 322

Using adaptive learning technologies to personalize instruction to student interests: The impact of relevant contexts on performance and learning outcomes

Walkington, C. A. (2013) · Journal of Educational Psychology

Intelligent Tutoring Systems and Adaptive LearningInnovative Teaching and Learning Methods

Cited by 322

A survey of software learnability: metrics, methodologies and guidelines

Grossman, T., Fitzmaurice, G., & Attar, R. (2009) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Usability and User Interface DesignInnovative Human-Technology Interaction

Cited by 322

What to account for when accounting for algorithms: a systematic literature review on algorithmic accountability

Wieringa, M. (2020) · Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency

Ethics and Social Impacts of AIDigitalization, Law, and Regulation

Cited by 321

Open PHACTS: semantic interoperability for drug discovery

Williams, A. J., Harland, L., Groth, P., Pettifer, S., Chichester, C., Willighagen, E. L., Evelo, C. T., Blomberg, N., Ecker, G., Goble, C., et al. (2012) · Drug Discovery Today

Semantic Web and OntologiesBiomedical Text Mining and Ontologies

Cited by 321

Object Goal Navigation using Goal-Oriented Semantic Exploration

Chaplot, D. S., Gandhi, D., Gupta, A., & Salakhutdinov, R. (2020) · arXiv

Reinforcement Learning in RoboticsRobotics and Sensor-Based Localization

Cited by 321

Deep Roots: Improving CNN Efficiency with Hierarchical Filter Groups

Ioannou, Y., Robertson, D., Cipolla, R., & Criminisi, A. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 321

Spectral–Spatial Hyperspectral Image Classification via Multiscale Adaptive Sparse Representation

Fang, L., Li, S., Kang, X., & Benediktsson, J. A. (2014) · IEEE Transactions on Geoscience and Remote Sensing

Remote-Sensing Image ClassificationFace and Expression Recognition

Cited by 321

Full spectrum sharing in cognitive radio networks toward 5G: a survey

Hu, F., Chen, B., & Zhu, K. (2018) · IEEE Access

Cognitive Radio Networks and Spectrum SensingVehicular Ad Hoc Networks (VANETs)

Cited by 321

Protovis: A Graphical Toolkit for Visualization

Bostock, M., & Heer, J. (2009) · IEEE Transactions on Visualization and Computer Graphics

Data Visualization and AnalyticsComputer Graphics and Visualization Techniques

Cited by 321

Moral crumple zones: cautionary tales in human–robot interaction

Elish, M. C. (2019) · Engaging Science, Technology, and Society

Ethics and Social Impacts of AIDigitalization, Law, and Regulation

Cited by 321

Machine translation of cortical activity to text with an encoder–decoder framework

Makin, J. G., Moses, D. A., & Chang, E. F. (2020) · Nature Neuroscience

Speech Recognition and SynthesisEEG and Brain-Computer Interfaces

Cited by 321