Check computer science papers: citations, claims and retractions

Approaching the human in the loop – legal perspectives on hybrid human/algorithmic decision-making in three contexts

Enarsson, T., Enqvist, L., & Naarttijärvi, M. (2022) · Information & Communications Technology Law

Ethics and Social Impacts of AIDigitalization, Law, and Regulation

Cited by 113

A Capacity Result for Batch Steganography

Ker, A. D. (2007) · IEEE Signal Processing Letters

Advanced Steganography and Watermarking TechniquesWireless Communication Security Techniques

Cited by 113

Random Walks for Interactive Organ Segmentation in Two and Three Dimensions: Implementation and Validation

Grady, L., Schiwietz, T., Aharon, S., & Westermann, R. (2005) · Lecture Notes in Computer Science

Medical Image Segmentation TechniquesMedical Imaging and Analysis

Cited by 113

Visual Tracking via Probability Continuous Outlier Model

Wang, D., & Lu, H. (2014) · 2014 IEEE Conference on Computer Vision and Pattern Recognition

Video Surveillance and Tracking MethodsAdvanced Vision and Imaging

Cited by 113

An artificial intelligence-based chest x-ray model on human nodule detection accuracy from a multicenter study

Homayounieh, F., Digumarthy, S., Ebrahimian, S., Rueckel, J., Hoppe, B. F., Sabel, B. O., Conjeti, S., Ridder, K., Sistermanns, M., Wang, L., et al. (2021) · JAMA Network Open

AI in cancer detectionLung Cancer Diagnosis and Treatment

Cited by 113

Emotion recognition from facial expression using deep convolutional neural network

Liliana, D. Y. (2019) · Journal of Physics: Conference Series

Emotion and Mood RecognitionFace recognition and analysis

Cited by 113

Mapping Twitter hate speech towards social and sexual minorities: a lexicon-based approach to semantic content analysis

Lingiardi, V., Carone, N., Semeraro, G., Musto, C., D’Amico, M., & Brena, S. (2020) · Behaviour & Information Technology

Hate Speech and Cyberbullying DetectionSentiment Analysis and Opinion Mining

Cited by 113

Students’ perceptions of, and emotional responses to, personalised learning analytics-based feedback: an exploratory study of four courses

Lim, L.-A., Dawson, S., Gašević, D., Joksimović, S., Pardo, A., Fudge, A., & Gentili, S. (2021) · Assessment & Evaluation in Higher Education

Online Learning and AnalyticsStudent Assessment and Feedback

Cited by 113

S3: Social-network Simulation System with Large Language Model-Empowered Agents

Gao, C., Lan, X., Lu, Z., Mao, J., Piao, J., Wang, H., Jin, D., & Li, Y. (2023) · SSRN Electronic Journal

Multi-Agent Systems and NegotiationOpinion Dynamics and Social Influence

Cited by 113

Deepfake Media Forensics: Status and Future Challenges

Amerini, I., Barni, M., Battiato, S., Bestagini, P., Boato, G., Bruni, V., Caldelli, R., De Natale, F., De Nicola, R., Guarnera, L., et al. (2025) · Journal of Imaging

Digital Media Forensic DetectionMisinformation and Its Impacts

Cited by 113

Steiner tree based optimal resource caching scheme in fog computing

Su, J., Lin, F., Zhou, X., & Lu, X. (2015) · China Communications

Caching and Content DeliveryIoT and Edge/Fog Computing

Cited by 113

Validation of the Amsterdam Dynamic Facial Expression Set – Bath Intensity Variations (ADFES-BIV): A Set of Videos Expressing Low, Intermediate, and High Intensity Emotions

Wingenbach, T. S. H., Ashwin, C., & Brosnan, M. (2016) · PLOS ONE

Emotion and Mood RecognitionFace Recognition and Perception

Cited by 113

Blockchain Based Autonomous Selection of Electric Vehicle Charging Station

Pustisek, M., Kos, A., & Sedlar, U. (2016) · 2016 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI)

Blockchain Technology Applications and SecurityElectric Vehicles and Infrastructure

Cited by 113

Dilated FCN for Multi-Agent 2D/3D Medical Image Registration

Miao, S., Piat, S., Fischer, P., Tuysuzoglu, A., Mewes, P., Mansi, T., & Liao, R. (2018) · Proceedings of the AAAI Conference on Artificial Intelligence

Medical Image Segmentation TechniquesMedical Imaging and Analysis

Cited by 113

Medical Image Segmentation: Methods and Software

Withey, D. J., & Koles, Z. J. (2007) · 2007 Joint Meeting of the 6th International Symposium on Noninvasive Functional Source Imaging of the Brain and Heart and the International Conference on Functional Biomedical Imaging

Medical Image Segmentation TechniquesMedical Imaging and Analysis

Cited by 113

ColloSSL: Collaborative Self-Supervised Learning for Human Activity Recognition

Jain, Y., Tang, C. I., Min, C., Kawsar, F., & Mathur, A. (2022) · Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Context-Aware Activity Recognition SystemsDomain Adaptation and Few-Shot Learning

Cited by 113

A hybrid system for reducing the false alarm rate of anomaly intrusion detection system

Om, H., & Kundu, A. (2012) · 2012 1st International Conference on Recent Advances in Information Technology (RAIT)

Network Security and Intrusion DetectionArtificial Immune Systems Applications

Cited by 113

MindMap: Knowledge Graph Prompting Sparks Graph of Thoughts in Large Language Models

Wen, Y., Wang, Z., & Sun, J. (2023) · arXiv

Topic ModelingMultimodal Machine Learning Applications

Cited by 113

An AI-based open recommender system for personalized labor market driven education

Tavakoli, M., Faraji, A., Vrolijk, J., Molavi, M., Mol, S. T., & Kismihók, G. (2022) · Advanced Engineering Informatics

Recommender Systems and TechniquesOnline Learning and Analytics

Cited by 113

Using fNIRS brain sensing to evaluate information visualization interfaces

Peck, E. M. M., Yuksel, B. F., Ottley, A., Jacob, R. J. K., & Chang, R. (2013) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Data Visualization and AnalyticsOptical Imaging and Spectroscopy Techniques

Cited by 113

Dynamic Trees for Learning and Design

Taddy, M. A., Gramacy, R. B., & Polson, N. G. (2011) · Journal of the American Statistical Association

Gaussian Processes and Bayesian InferenceStatistical Methods and Inference

Cited by 113

Frozen Pretrained Transformers as Universal Computation Engines

Lu, K., Grover, A., Abbeel, P., & Mordatch, I. (2022) · Proceedings of the AAAI Conference on Artificial Intelligence

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 113

Deep predictive policy training using reinforcement learning

Ghadirzadeh, A., Maki, A., Kragic, D., & Bjorkman, M. (2017) · 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 113

Edge AI for Early Detection of Chronic Diseases and the Spread of Infectious Diseases: Opportunities, Challenges, and Future Directions

Badidi, E. (2023) · Future Internet

IoT and Edge/Fog ComputingInternet of Things and AI

Cited by 113