Check computer science papers: citations, claims and retractions

Blind omnidirectional image quality assessment with viewport oriented graph convolutional networks

Xu, J., Zhou, W., & Chen, Z. (2021) · IEEE Transactions on Circuits and Systems for Video Technology

Image and Video Quality AssessmentImage Retrieval and Classification Techniques

Cited by 166

Self-supervised learning for human activity recognition using 700,000 person-days of wearable data

Yuan, H., Chan, S., Creagh, A. P., Tong, C., Acquah, A., Clifton, D. A., & Doherty, A. (2024) · npj Digital Medicine

Context-Aware Activity Recognition SystemsPhysical Activity and Health

Cited by 166

A Monolingual Approach to Contextualized Word Embeddings for Mid-Resource Languages

Ortiz Suárez, P. J., Romary, L., & Sagot, B. (2020) · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics

Natural Language Processing TechniquesTopic Modeling

Cited by 166

Did the Model Understand the Question?

Mudrakarta, P. K., Taly, A., Sundararajan, M., & Dhamdhere, K. (2018) · Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Adversarial Robustness in Machine LearningExplainable Artificial Intelligence (XAI)

Cited by 166

Privacy‐Aware Multidimensional Mobile Service Quality Prediction and Recommendation in Distributed Fog Environment

Gong, W., Qi, L., & Xu, Y. (2018) · Wireless Communications and Mobile Computing

Recommender Systems and TechniquesPrivacy-Preserving Technologies in Data

Cited by 166

On the classification of emotional biosignals evoked while viewing affective pictures: An integrated data-mining-based approach for healthcare applications

Frantzidis, C. A., Bratsas, C., Klados, M. A., Konstantinidis, E., Lithari, C. D., Vivas, A. B., Papadelis, C. L., Kaldoudi, E., Pappas, C., & Bamidis, P. D. (2010) · IEEE Transactions on Information Technology in Biomedicine

Emotion and Mood RecognitionHeart Rate Variability and Autonomic Control

Cited by 166

Participatory Design, User Involvement and Health IT Evaluation

Andre, K., & Christian, N. (2016) · Studies in Health Technology and Informatics

Usability and User Interface DesignElectronic Health Records Systems

Cited by 166

Understanding Membership Inferences on Well-Generalized Learning Models

Long, Y., Bindschaedler, V., Wang, L., Bu, D., Wang, X., Tang, H., Gunter, C. A., & Chen, K. (2018) · arXiv

Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data

Cited by 166

Hallusionbench: An Advanced Diagnostic Suite for Entangled Language Hallucination and Visual Illusion in Large Vision-Language Models

Guan, T., Liu, F., Wu, X., Xian, R., Li, Z., Liu, X., Wang, X., Chen, L., Huang, F., Yacoob, Y., et al. (2024) · 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Multimodal Machine Learning ApplicationsAdvanced Neural Network Applications

Cited by 166

Retrieve and Refine: Improved Sequence Generation Models For Dialogue

Weston, J., Dinan, E., & Miller, A. (2018) · Proceedings of the 2018 EMNLP Workshop SCAI: The 2nd International Workshop on Search-Oriented Conversational AI

Speech and dialogue systemsTopic Modeling

Cited by 165

MIMIC-III Clinical Database

Johnson, A., Pollard, T., & Mark, R. (2015) · PhysioNet

Machine Learning in HealthcareSepsis Diagnosis and Treatment

Cited by 165

Handling privacy-sensitive medical data with federated learning: Challenges and future directions

Aouedi, O., Sacco, A., Piamrat, K., & Marchetto, G. (2023) · IEEE Journal of Biomedical and Health Informatics

Privacy-Preserving Technologies in DataArtificial Intelligence in Healthcare and Education

Cited by 165

Personalizing Dialogue Agents: I have a dog, do you have pets too?

Zhang, S., Dinan, E., Urbanek, J., Szlam, A., Kiela, D., & Weston, J. (2018) · arXiv

Speech and dialogue systemsAI in Service Interactions

Cited by 165

Cloudlets: at the Leading Edge of Mobile-Cloud Convergence

Satyanarayanan, M., Chen, Z., Ha, K., Hu, W., Richter, W., & Pillai, P. (2014) · Proceedings of the 6th International Conference on Mobile Computing, Applications and Services

IoT and Edge/Fog ComputingCloud Computing and Remote Desktop Technologies

Cited by 165

Theoretical Limitations of Self-Attention in Neural Sequence Models

Hahn, M. (2020) · Transactions of the Association for Computational Linguistics

Natural Language Processing Techniquessemigroups and automata theory

Cited by 165

Interactive collaborative filtering

Zhao, X., Zhang, W., & Wang, J. (2013) · Proceedings of the 22nd ACM international conference on Information & Knowledge Management

Recommender Systems and TechniquesAdvanced Bandit Algorithms Research

Cited by 165

Reproducible and reusable research: are journal data sharing policies meeting the mark?

Vasilevsky, N. A., Minnier, J., Haendel, M. A., & Champieux, R. E. (2017) · PeerJ

Research Data Management PracticesAcademic Publishing and Open Access

Cited by 165

XNOR-Net++: Improved Binary Neural Networks

Bulat, A., & Tzimiropoulos, G. (2019) · arXiv

Advanced Neural Network ApplicationsAdvanced Memory and Neural Computing

Cited by 165

Detection and Mitigation of DoS and DDoS Attacks in IoT-Based Stateful SDN: An Experimental Approach

Galeano-Brajones, J., Carmona-Murillo, J., Valenzuela-Valdés, J. F., & Luna-Valero, F. (2020) · Sensors

Network Security and Intrusion DetectionSoftware-Defined Networks and 5G

Cited by 165

An overview of decentralized autonomous organizations on the blockchain

El Faqir, Y., Arroyo, J., & Hassan, S. (2020) · Proceedings of the 16th International Symposium on Open Collaboration

Blockchain Technology Applications and SecurityBlockchain Technology in Education and Learning

Cited by 165

Convolutional neural network regression for short-axis left ventricle segmentation in cardiac cine MR sequences

Tan, L. K., Liew, Y. M., Lim, E., & McLaughlin, R. A. (2017) · Medical Image Analysis

Medical Image Segmentation TechniquesCardiac Imaging and Diagnostics

Cited by 165

Multimodal data integration for oncology in the era of deep neural networks: a review

Waqas, A., Tripathi, A., Ramachandran, R. P., Stewart, P. A., & Rasool, G. (2024) · Frontiers in Artificial Intelligence

Multimodal Machine Learning ApplicationsAI in cancer detection

Cited by 165

Embedded Real-time Stereo Estimation via Semi-global Matching on the GPU

Hernandez-Juarez, D., Chacón, A., Espinosa, A., Vázquez, D., Moure, J. C., & López, A. M. (2016) · Procedia Computer Science

Advanced Vision and ImagingRobotics and Sensor-Based Localization

Cited by 165

DeepSOFA: a continuous acuity score for critically ill patients using clinically interpretable deep learning.

Shickel, B., Loftus, T. J., Adhikari, L., Ozrazgat-Baslanti, T., Bihorac, A., & Rashidi, P. (2019) · Scientific Reports

Machine Learning in HealthcareSepsis Diagnosis and Treatment

Cited by 165