Check computer science papers: citations, claims and retractions

Game AI revisited

Yannakakis, G. N. (2012) · Proceedings of the 9th conference on Computing Frontiers

Artificial Intelligence in GamesArtificial Intelligence Applications

Cited by 179

RSVG: Exploring Data and Models for Visual Grounding on Remote Sensing Data

Zhan, Y., Xiong, Z., & Yuan, Y. (2023) · IEEE Transactions on Geoscience and Remote Sensing

Multimodal Machine Learning ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 179

MART: Memory-Augmented Recurrent Transformer for Coherent Video Paragraph Captioning

Lei, J., Wang, L., Shen, Y., Yu, D., Berg, T., & Bansal, M. (2020) · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics

Multimodal Machine Learning ApplicationsVideo Analysis and Summarization

Cited by 179

Quality at a Glance: An Audit of Web-Crawled Multilingual Datasets

Kreutzer, J., Caswell, I., Wang, L., Wahab, A., van Esch, D., Ulzii-Orshikh, N., Tapo, A., Subramani, N., Sokolov, A., Sikasote, C., et al. (2022) · Transactions of the Association for Computational Linguistics

Natural Language Processing TechniquesTopic Modeling

Cited by 179

Logic Tensor Networks for Semantic Image Interpretation

Donadello, I., Serafini, L., & d'Avila Garcez, A. (2017) · Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence

Advanced Neural Network ApplicationsLogic, Reasoning, and Knowledge

Cited by 179

Deep Recursive Network Embedding with Regular Equivalence

Tu, K., Cui, P., Wang, X., Yu, P. S., & Zhu, W. (2018) · Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

Advanced Graph Neural NetworksComplex Network Analysis Techniques

Cited by 179

Using online, crowdsourcing platforms for data collection in personality disorder research: the example of Amazon’s Mechanical Turk

Miller, J. D., Crowe, M., Weiss, B., Maples-Keller, J. L., & Lynam, D. R. (2017) · Personality Disorders Theory Research and Treatment

Mobile Crowdsensing and CrowdsourcingPersonality Disorders and Psychopathology

Cited by 179

Measuring All Compatible Operators in One Series of Single-Qubit Measurements Using Unitary Transformations

Yen, T.-C., Verteletskyi, V., & Izmaylov, A. F. (2020) · Journal of Chemical Theory and Computation

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 178

Scalable Game Design: A Strategy to Bring Systemic Computer Science Education to Schools through Game Design and Simulation Creation

Repenning, A., Webb, D. C., Koh, K. H., Nickerson, H., Miller, S. B., Brand, C., Horses, I. H. M., Basawapatna, A., Gluck, F., Grover, R., et al. (2015) · ACM Transactions on Computing Education

Teaching and Learning ProgrammingEducational Games and Gamification

Cited by 178

Big Data Privacy Preserving in Multi-Access Edge Computing for Heterogeneous Internet of Things

Du, M., Wang, K., Chen, Y., Wang, X., & Sun, Y. (2018) · IEEE Communications Magazine

IoT and Edge/Fog ComputingPrivacy-Preserving Technologies in Data

Cited by 178

Optimal resources for topological two-dimensional stabilizer codes: Comparative study

Bombin, H., & Martin-Delgado, M. A. (2007) · Physical Review A

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 178

Digital Currencies, Decentralized Ledgers, and the Future of Central Banking

Raskin, M., & Yermack, D. (2016) · National Bureau of Economic Research

Blockchain Technology Applications and SecurityDigital Transformation in Financial Services

Cited by 178

Blockchain technology toward green IoT: opportunities and challenges

Sharma, P. K., Kumar, N., & Park, J. H. (2020) · IEEE Network

Blockchain Technology Applications and SecurityInternet of Things and AI

Cited by 178

Deep learning-based unlearning of dataset bias for mri harmonisation and confound removal

Dinsdale, N. K., Jenkinson, M., & Namburete, A. I. L. (2021) · NeuroImage

Domain Adaptation and Few-Shot LearningAdvanced MRI Techniques and Applications

Cited by 178

Brain Tumor Detection by Using Stacked Autoencoders in Deep Learning

Amin, J., Sharif, M., Gul, N., Raza, M., Anjum, M. A., Nisar, M. W., & Bukhari, S. A. C. (2020) · Journal of Medical Systems

Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques

Cited by 178

Scene Memory Transformer for Embodied Agents in Long-Horizon Tasks

Fang, K., Toshev, A., Fei-Fei, L., & Savarese, S. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Reinforcement Learning in RoboticsAI-based Problem Solving and Planning

Cited by 178

New Potentials for Data‐Driven Intelligent Tutoring System Development and Optimization

Koedinger, K. R., Brunskill, E., Baker, R. S. J. D., McLaughlin, E. A., & Stamper, J. (2013) · AI Magazine

Intelligent Tutoring Systems and Adaptive LearningOnline Learning and Analytics

Cited by 178

Privacy-preserved task offloading in mobile blockchain with deep reinforcement learning

Nguyen, D. C., Pathirana, P. N., Ding, M., & Seneviratne, A. (2020) · IEEE Transactions on Network and Service Management

IoT and Edge/Fog ComputingBlockchain Technology Applications and Security

Cited by 178

Neural Map: Structured Memory for Deep Reinforcement Learning

Parisotto, E., & Salakhutdinov, R. (2017) · arXiv

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 178

ASVspoof 2017 Version 2.0: meta-data analysis and baseline enhancements

Delgado, H., Todisco, M., Sahidullah, M., Evans, N., Kinnunen, T., Lee, K. A., & Yamagishi, J. (2018) · The Speaker and Language Recognition Workshop (Odyssey 2018)

Speech Recognition and SynthesisBiometric Identification and Security

Cited by 178

Unmasking bias in artificial intelligence: A systematic review of bias detection and mitigation strategies in electronic health record-based models

Chen, F., Wang, L., Hong, J., Jiang, J., & Zhou, L. (2024) · Journal of the American Medical Informatics Association

Ethics and Social Impacts of AIArtificial Intelligence in Healthcare and Education

Cited by 178

Domain Adversarial for Acoustic Emotion Recognition

Abdelwahab, M., & Busso, C. (2018) · IEEE/ACM Transactions on Audio, Speech, and Language Processing

Emotion and Mood RecognitionDomain Adaptation and Few-Shot Learning

Cited by 178

Do We Need More Training Data or Better Models for Object Detection?

Zhu, X., Vondrick, C., Ramanan, D., & Fowlkes, C. (2012) · Procedings of the British Machine Vision Conference 2012

Advanced Image and Video Retrieval TechniquesAdvanced Neural Network Applications

Cited by 178

Robotic Waste Sorting Technology: Toward a Vision-Based Categorization System for the Industrial Robotic Separation of Recyclable Waste

Koskinopoulou, M., Raptopoulos, F., Papadopoulos, G., Mavrakis, N., & Maniadakis, M. (2021) · IEEE Robotics & Automation Magazine

Advanced Neural Network ApplicationsRobot Manipulation and Learning

Cited by 178