Check computer science papers: citations, claims and retractions

Learning Pattern Classification Tasks with Imbalanced Data Sets

Hoang, G., Bouzerdoum, A., & Lam, S. (2009) · Pattern Recognition

Imbalanced Data Classification TechniquesMachine Learning and Data Classification

Cited by 178

Deep semantic segmentation for automated driving: Taxonomy, roadmap and challenges

Siam, M., Elkerdawy, S., Jagersand, M., & Yogamani, S. (2017) · 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC)

Advanced Neural Network ApplicationsAutonomous Vehicle Technology and Safety

Cited by 178

Generative adversarial networks–enabled human–artificial intelligence collaborative applications for creative and design industries: A systematic review of current approaches and trends.

Hughes, R. T., Zhu, L., & Bednarz, T. (2021) · Frontiers in Artificial Intelligence

Generative Adversarial Networks and Image SynthesisDigital Media and Visual Art

Cited by 178

ChaCha20 and Poly1305 for IETF Protocols

Nir, Y., & Langley, A. (2018)

Cryptographic Implementations and SecurityCryptography and Residue Arithmetic

Cited by 178

Fast and reliable structure-oriented video noise estimation

Amer, A., & Dubois, E. (2005) · IEEE Transactions on Circuits and Systems for Video Technology

Image and Video Quality AssessmentImage and Signal Denoising Methods

Cited by 178

A Survey of Paraphrasing and Textual Entailment Methods

Androutsopoulos, I., & Malakasiotis, P. (2010) · Journal of Artificial Intelligence Research

Natural Language Processing TechniquesTopic Modeling

Cited by 178

Towards Understanding Ensemble, Knowledge Distillation and Self-Distillation in Deep Learning

Allen-Zhu, Z., & Li, Y. (2020) · arXiv

Domain Adaptation and Few-Shot LearningMachine Learning and Algorithms

Cited by 178

Deep Learning-Based Anomaly Detection in Video Surveillance: A Survey

Duong, H.-T., Le, V.-T., & Hoang, V. T. (2023) · Sensors

Anomaly Detection Techniques and ApplicationsHuman Pose and Action Recognition

Cited by 178

Fitts' law and expanding targets: Experimental studies and designs for user interfaces

McGuffin, M. J., & Balakrishnan, R. (2005) · ACM Transactions on Computer-Human Interaction

Interactive and Immersive DisplaysUsability and User Interface Design

Cited by 178

Explainable AI and machine learning: performance evaluation and explainability of classifiers on educational data mining inspired career counseling

Guleria, P., & Sood, M. (2023) · Education and Information Technologies

Online Learning and AnalyticsExplainable Artificial Intelligence (XAI)

Cited by 178

HRFormer: High-Resolution Transformer for Dense Prediction

Yuan, Y., Fu, R., Huang, L., Lin, W., Zhang, C., Chen, X., & Wang, J. (2021) · arXiv

Advanced Neural Network ApplicationsHuman Pose and Action Recognition

Cited by 178

Text Categorization Models for High-Quality Article Retrieval in Internal Medicine

Aphinyanaphongs, Y. (2004) · Journal of the American Medical Informatics Association

Information Retrieval and Search BehaviorText and Document Classification Technologies

Cited by 177

Distinction between benign and malignant breast masses at breast ultrasound using deep learning method with convolutional neural network

Fujioka, T., Kubota, K., Mori, M., Kikuchi, Y., Katsuta, L., Kasahara, M., Oda, G., Ishiba, T., Nakagawa, T., & Tateishi, U. (2019) · Japanese Journal of Radiology

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 177

Sara, the Lecturer: Improving Learning in Online Education with a Scaffolding-Based Conversational Agent

Winkler, R., Hobert, S., Salovaara, A., Söllner, M., & Leimeister, J. M. (2020) · Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Intelligent Tutoring Systems and Adaptive LearningVisual and Cognitive Learning Processes

Cited by 177

STransE: a novel embedding model of entities and relationships in knowledge bases

Nguyen, D. Q., Sirts, K., Qu, L., & Johnson, M. (2016) · Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Advanced Graph Neural NetworksTopic Modeling

Cited by 177

Moral foundations twitter corpus: a collection of 35k tweets annotated for moral sentiment

Hoover, J., Portillo-Wightman, G., Yeh, L., Havaldar, S., Davani, A. M., Lin, Y., Kennedy, B., Atari, M., Kamel, Z., Mendlen, M., et al. (2020) · Social Psychological and Personality Science

Sentiment Analysis and Opinion MiningHate Speech and Cyberbullying Detection

Cited by 177

Efficient Large-Scale Multi-Modal Classification

Kiela, D., Grave, E., Joulin, A., & Mikolov, T. (2018) · Proceedings of the AAAI Conference on Artificial Intelligence

Multimodal Machine Learning ApplicationsAdvanced Neural Network Applications

Cited by 177

Reproducibility of Benchmarked Deep Reinforcement Learning Tasks for Continuous Control

Islam, R., Henderson, P., Gomrokchi, M., & Precup, D. (2017) · arXiv

Reinforcement Learning in RoboticsAdaptive Dynamic Programming Control

Cited by 177

Neural Articulated Radiance Field

Noguchi, A., Sun, X., Lin, S., & Harada, T. (2021) · arXiv

3D Shape Modeling and AnalysisComputer Graphics and Visualization Techniques

Cited by 177

Blockchain-based efficient privacy preserving and data sharing scheme of content-centric network in 5G

Fan, K., Ren, Y., Wang, Y., Li, H., & Yang, Y. (2018) · IET Communications

Blockchain Technology Applications and SecurityCaching and Content Delivery

Cited by 177

eFraudCom: An E-commerce Fraud Detection System via Competitive Graph Neural Networks

Zhang, G., Li, Z., Huang, J., Wu, J., Zhou, C., Yang, J., & Gao, J. (2022) · ACM Transactions on Information Systems

Spam and Phishing DetectionAdvanced Graph Neural Networks

Cited by 177

Equipping community health workers with digital tools for pandemic response in LMICs

Feroz, A. S., Khoja, A., & Saleem, S. (2021) · Archives of Public Health

ICT in Developing CommunitiesCOVID-19 Digital Contact Tracing

Cited by 177

Quantum Optimization and Quantum Learning: A Survey

Li, Y., Tian, M., Liu, G., Peng, C., & Jiao, L. (2020) · IEEE Access

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 177

A learning-based wrapper method to correct systematic errors in automatic image segmentation: Consistently improved performance in hippocampus, cortex and brain segmentation

Wang, H., Das, S. R., Suh, J. W., Altinay, M., Pluta, J., Craige, C., Avants, B., & Yushkevich, P. A. (2011) · NeuroImage

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 177