Check computer science papers: citations, claims and retractions

Deep-Learning-Enhanced Multitarget Detection for End–Edge–Cloud Surveillance in Smart IoT

Zhou, X., Xu, X., Liang, W., Zeng, Z., & Yan, Z. (2021) · IEEE Internet of Things Journal

Advanced Neural Network ApplicationsVideo Surveillance and Tracking Methods

Cited by 332

Layered architecture for quantum computing

Jones, N. C., Van Meter, R., Fowler, A. G., McMahon, P. L., Kim, J., Ladd, T. D., & Yamamoto, Y. (2012) · Physical Review X

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 332

The Quaternion LMS Algorithm for Adaptive Filtering of Hypercomplex Processes

Took, C. C., & Mandic, D. P. (2009) · IEEE Transactions on Signal Processing

Advanced Adaptive Filtering TechniquesAlgebraic and Geometric Analysis

Cited by 332

When internet of things meets blockchain: Challenges in distributed consensus

Cao, B., Li, Y., Zhang, L., Zhang, L., Mumtaz, S., Zhou, Z., & Peng, M. (2019) · IEEE Network

Blockchain Technology Applications and SecurityBlockchain Technology in Education and Learning

Cited by 332

Quantum Supremacy through the Quantum Approximate Optimization Algorithm

Farhi, E., & Harrow, A. W. (2016) · arXiv

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 331

Creating Large Language Model Applications Utilizing LangChain: A Primer on Developing LLM Apps Fast

Topsakal, O., & Akinci, T. C. (2023) · International Conference on Applied Engineering and Natural Sciences

Topic ModelingArtificial Intelligence Applications

Cited by 331

Can Large Language Models Be an Alternative to Human Evaluations?

Chiang, C.-H., & Lee, H.-Y. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 331

A survey on data‐efficient algorithms in big data era

Adadi, A. (2021) · Journal of Big Data

Domain Adaptation and Few-Shot LearningMachine Learning and Algorithms

Cited by 331

ANTIDOTE: understanding and defending against poisoning of anomaly detectors

Rubinstein, B. I. P., Nelson, B., Huang, L., Joseph, A. D., Lau, S.-H., Rao, S., Taft, N., & Tygar, J. D. (2009) · Proceedings of the 9th ACM SIGCOMM conference on Internet measurement

Adversarial Robustness in Machine LearningNetwork Security and Intrusion Detection

Cited by 331

Biometric State: The Global Politics of Identification and Surveillance in South Africa, 1850 to the Present

Breckenridge, K. (2014) · Cambridge University Press eBooks

Biometric Identification and SecuritySouth African History and Culture

Cited by 331

Presence within Virtual Environments as a Function of Visual Display Parameters

Hendrix, C., & Barfield, W. (1996) · Presence: Teleoperators and Virtual Environments

Virtual Reality Applications and ImpactsSocial Robot Interaction and HRI

Cited by 331

MoDNN: Local distributed mobile computing system for Deep Neural Network

Mao, J., Chen, X., Nixon, K. W., Krieger, C., & Chen, Y. (2017) · Design, Automation & Test in Europe Conference & Exhibition (DATE), 2017

IoT and Edge/Fog ComputingParallel Computing and Optimization Techniques

Cited by 331

The Affective Response Model: A Theoretical Framework of Affective Concepts and Their Relationships in the ICT Context1

Zhang, P. (2013) · MIS Quarterly

Innovative Human-Technology InteractionTechnology Adoption and User Behaviour

Cited by 331

RGB-D salient object detection: A survey

Zhou, T., Fan, D.-P., Cheng, M.-M., Shen, J., & Shao, L. (2021) · Computational Visual Media

Visual Attention and Saliency DetectionAdvanced Neural Network Applications

Cited by 331

Can Large Language Models Be an Alternative to Human Evaluations?

Chiang, C.-H., & Lee, H.-Y. (2023) · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 331

Quantum walks on a programmable two-dimensional 62-qubit superconducting processor

Gong, M., Wang, S., Zha, C., Chen, M.-C., Huang, H.-L., Wu, Y., Zhu, Q., Zhao, Y., Li, S., Guo, S., et al. (2021) · Science

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 331

The Effects of Data Quality on Machine Learning Performance on Tabular Data

Mohammed, S., Budach, L., Feuerpfeil, M., Ihde, N., Nathansen, A., Noack, N., Patzlaff, H., Naumann, F., & Harmouch, H. (2025) · Information Systems

Data Quality and ManagementMachine Learning and Data Classification

Cited by 331

Deep learning in robotics: A review of recent research

Pierson, H. A., & Gashler, M. S. (2017) · Advanced Robotics

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 331

Detecting GAN generated Fake Images using Co-occurrence Matrices

Nataraj, L., Mohammed, T. M., Manjunath, B. S., Chandrasekaran, S., Flenner, A., Bappy, J. H., & Roy-Chowdhury, A. K. (2019) · Electronic Imaging

Digital Media Forensic DetectionGenerative Adversarial Networks and Image Synthesis

Cited by 331

Augmenting organizational decision-making with deep learning algorithms: principles, promises, and challenges

Shrestha, Y. R., Krishna, V., & von Krogh, G. (2021) · Journal of Business Research

Artificial Intelligence ApplicationsImpact of AI and Big Data on Business and Society

Cited by 331

Implicit Quantile Networks for Distributional Reinforcement Learning

Dabney, W., Ostrovski, G., Silver, D., & Munos, R. (2018) · arXiv

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 331

Artificial intelligence governance: Ethical considerations and implications for social responsibility

Camilleri, M. A. (2024) · Expert Systems

Ethics and Social Impacts of AIDigitalization, Law, and Regulation

Cited by 331

REVERIE: Remote Embodied Visual Referring Expression in Real Indoor Environments

Qi, Y., Wu, Q., Anderson, P., Wang, X., Wang, W. Y., Shen, C., & van den Hengel, A. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Multimodal Machine Learning ApplicationsRobot Manipulation and Learning

Cited by 331

Audioclip: Extending Clip to Image, Text and Audio

Guzhov, A., Raue, F., Hees, J., & Dengel, A. (2022) · ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Music and Audio ProcessingDomain Adaptation and Few-Shot Learning

Cited by 330