Check computer science papers: citations, claims and retractions

Exploit All the Layers: Fast and Accurate CNN Object Detector with Scale Dependent Pooling and Cascaded Rejection Classifiers

Yang, F., Choi, W., & Lin, Y. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 608

OCGAN: One-Class Novelty Detection Using GANs With Constrained Latent Representations

Perera, P., Nallapati, R., & Xiang, B. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Anomaly Detection Techniques and ApplicationsAdversarial Robustness in Machine Learning

Cited by 608

Neuroscience of virtual reality: from virtual exposure to embodied medicine

Riva, G., Wiederhold, B. K., & Mantovani, F. (2019) · Cyberpsychology, Behavior, and Social Networking

Virtual Reality Applications and ImpactsDigital Mental Health Interventions

Cited by 608

Fundamentals of physiological computing

Fairclough, S. H. (2009) · Interacting with Computers

Emotion and Mood RecognitionInnovative Human-Technology Interaction

Cited by 608

ReAct: Synergizing Reasoning and Acting in Language Models

Yao, S., Zhao, J., Yu, D., Du, N., Shafran, I., Narasimhan, K., & Cao, Y. (2022) · arXiv

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 608

Improving Computer-Aided Detection UsingConvolutional Neural Networks and Random View Aggregation

Roth, H. R., Lu, L., Liu, J., Yao, J., Seff, A., Cherry, K., Kim, L., & Summers, R. M. (2016) · IEEE Transactions on Medical Imaging

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 608

Malware Obfuscation Techniques: A Brief Survey

You, I., & Yim, K. (2010) · 2010 International Conference on Broadband, Wireless Computing, Communication and Applications

Advanced Malware Detection TechniquesSecurity and Verification in Computing

Cited by 607

CNN Features off-the-shelf: an Astounding Baseline for Recognition

Razavian, A. S., Azizpour, H., Sullivan, J., & Carlsson, S. (2014) · arXiv

Advanced Image and Video Retrieval TechniquesAdvanced Neural Network Applications

Cited by 607

Towards Post-Quantum Blockchain: A Review on Blockchain Cryptography Resistant to Quantum Computing Attacks

Fernandez-Carames, T. M., & Fraga-Lamas, P. (2020) · IEEE Access

Cryptography and Data SecurityBlockchain Technology Applications and Security

Cited by 607

On testing non-testable programs

Weyuker, E. J. (1982) · The Computer Journal

Software Testing and Debugging TechniquesSoftware Reliability and Analysis Research

Cited by 606

AggNet: Deep Learning From Crowds for Mitosis Detection in Breast Cancer Histology Images

Albarqouni, S., Baur, C., Achilles, F., Belagiannis, V., Demirci, S., & Navab, N. (2016) · IEEE Transactions on Medical Imaging

AI in cancer detectionCell Image Analysis Techniques

Cited by 606

Deep, Convolutional, and Recurrent Models for Human Activity Recognition Using Wearables

Hammerla, N. Y., Halloran, S., & Ploetz, T. (2016) · arXiv

Context-Aware Activity Recognition SystemsGait Recognition and Analysis

Cited by 606

Evaluating the quality of machine learning explanations: a survey on methods and metrics

Zhou, J., Gandomi, A. H., Chen, F., & Holzinger, A. (2021) · Electronics

Explainable Artificial Intelligence (XAI)Software Testing and Debugging Techniques

Cited by 606

Evaluating associativity in CPU caches

Hill, M. D., & Smith, A. J. (1989) · IEEE Transactions on Computers

Parallel Computing and Optimization TechniquesNetwork Packet Processing and Optimization

Cited by 606

Towards secure and privacy-preserving data sharing in e-Health systems via consortium blockchain

Zhang, A., & Lin, X. (2018) · Journal of Medical Systems

Blockchain Technology Applications and SecurityBlockchain Technology in Education and Learning

Cited by 606

Detecting Adversarial Samples from Artifacts

Feinman, R., Curtin, R. R., Shintre, S., & Gardner, A. B. (2017) · arXiv

Adversarial Robustness in Machine LearningDigital Media Forensic Detection

Cited by 606

The AIC model selection method applied to path analytic models compared using a d‐separation test

Shipley, B. (2013) · Ecology

Bayesian Modeling and Causal InferenceStatistical Methods and Inference

Cited by 606

Deep learning for wireless physical layer: Opportunities and challenges

Wang, T., Wen, C.-K., Wang, H., Gao, F., Jiang, T., & Jin, S. (2017) · China Communications

Wireless Signal Modulation ClassificationAdvanced Wireless Communication Techniques

Cited by 606

Twenty Years of Mixture of Experts

Yuksel, S. E., Wilson, J. N., & Gader, P. D. (2012) · IEEE Transactions on Neural Networks and Learning Systems

Bayesian Methods and Mixture ModelsGaussian Processes and Bayesian Inference

Cited by 606

Learning multiple visual domains with residual adapters

Rebuffi, S.-A., Bilen, H., & Vedaldi, A. (2017) · arXiv

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 605

Self-supervised learning in medicine and healthcare

Krishnan, R., Rajpurkar, P., & Topol, E. J. (2022) · Nature Biomedical Engineering

Machine Learning in HealthcareArtificial Intelligence in Healthcare and Education

Cited by 605

Detect What You Can: Detecting and Representing Objects Using Holistic Models and Body Parts

Chen, X., Mottaghi, R., Liu, X., Fidler, S., Urtasun, R., & Yuille, A. (2014) · 2014 IEEE Conference on Computer Vision and Pattern Recognition

Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 605

Galactica: A Large Language Model for Science

Taylor, R., Kardas, M., Cucurull, G., Scialom, T., Hartshorn, A., Saravia, E., Poulton, A., Kerkez, V., & Stojnic, R. (2022) · arXiv

Topic ModelingMultimodal Machine Learning Applications

Cited by 605

Intelligent tutoring systems: A systematic review of characteristics, applications, and evaluation methods

Mousavinasab, E., Zarifsanaiey, N., R. Niakan Kalhori, S., Rakhshan, M., Keikha, L., & Ghazi Saeedi, M. (2021) · Interactive Learning Environments

Intelligent Tutoring Systems and Adaptive LearningArtificial Intelligence in Education

Cited by 605