Check computer science papers: citations, claims and retractions

Deep learning modelling techniques: Current progress, applications, advantages, and challenges

Ahmed, S. F., Alam, M. S. B., Hassan, M., Rozbu, M. R., Ishtiak, T., Rafa, N., Mofijur, M., Shawkat Ali, A. B. M., & Gandomi, A. H. (2023) · Artificial Intelligence Review

Neural Networks and ApplicationsAdvanced Neural Network Applications

Cited by 1,079

VirtualWorlds as Proxy for Multi-object Tracking Analysis

Gaidon, A., Wang, Q., Cabon, Y., & Vig, E. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Video Surveillance and Tracking MethodsAdvanced Neural Network Applications

Cited by 1,079

Network Slicing and Softwarization: A Survey on Principles, Enabling Technologies, and Solutions

Afolabi, I., Taleb, T., Samdanis, K., Ksentini, A., & Flinck, H. (2018) · IEEE Communications Surveys & Tutorials

Software-Defined Networks and 5GAdvanced Optical Network Technologies

Cited by 1,078

A Review on the Use of Blockchain for the Internet of Things

Fernandez-Carames, T. M., & Fraga-Lamas, P. (2018) · IEEE Access

Blockchain Technology Applications and SecurityIoT and Edge/Fog Computing

Cited by 1,078

Align before Fuse: Vision and Language Representation Learning with Momentum Distillation

Li, J., Selvaraju, R. R., Gotmare, A. D., Joty, S., Xiong, C., & Hoi, S. (2021) · arXiv

Multimodal Machine Learning ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 1,078

DINOv2: Learning Robust Visual Features without Supervision

Oquab, M., Darcet, T., Moutakanni, T., Vo, H., Szafraniec, M., Khalidov, V., Fernandez, P., Haziza, D., Massa, F., El-Nouby, A., et al. (2023) · arXiv

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 1,078

Learning Analytics: Ethical Issues and Dilemmas

Slade, S., & Prinsloo, P. (2013) · American Behavioral Scientist

Online Learning and AnalyticsDigital Education and Society

Cited by 1,078

EIE: Efficient Inference Engine on Compressed Deep Neural Network

Han, S., Liu, X., Mao, H., Pu, J., Pedram, A., Horowitz, M. A., & Dally, W. J. (2016) · 2016 ACM/IEEE 43rd Annual International Symposium on Computer Architecture (ISCA)

Advanced Neural Network ApplicationsParallel Computing and Optimization Techniques

Cited by 1,077

A survey of blockchain from the perspectives of applications, challenges, and opportunities

Monrat, A. A., Schelen, O., & Andersson, K. (2019) · IEEE Access

Blockchain Technology Applications and SecurityBlockchain Technology in Education and Learning

Cited by 1,077

MoCoGAN: Decomposing Motion and Content for Video Generation

Tulyakov, S., Liu, M.-Y., Yang, X., & Kautz, J. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition

Generative Adversarial Networks and Image SynthesisAdvanced Image Processing Techniques

Cited by 1,076

Educational Applications of Metaverse: Possibilities and Limitations

Kye, B., Han, N., Kim, E., Park, Y., & Jo, S. (2021) · Journal of Educational Evaluation for Health Professions

Augmented Reality ApplicationsVirtual Reality Applications and Impacts

Cited by 1,076

iSAM: Incremental Smoothing and Mapping

Kaess, M., Ranganathan, A., & Dellaert, F. (2008) · IEEE Transactions on Robotics

Robotics and Sensor-Based LocalizationTarget Tracking and Data Fusion in Sensor Networks

Cited by 1,076

DIALOGPT : Large-Scale Generative Pre-training for Conversational Response Generation

Zhang, Y., Sun, S., Galley, M., Chen, Y.-C., Brockett, C., Gao, X., Gao, J., Liu, J., & Dolan, B. (2020) · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations

Speech and dialogue systemsTopic Modeling

Cited by 1,076

Automatic classification of single facial images

Lyons, M. J., Budynek, J., & Akamatsu, S. (1999) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Face and Expression RecognitionFace recognition and analysis

Cited by 1,075

Reliable Accuracy Estimates from k-Fold Cross Validation

Wong, T.-T., & Yeh, P.-Y. (2020) · IEEE Transactions on Knowledge and Data Engineering

Machine Learning and Data ClassificationData Mining and Machine Learning Applications

Cited by 1,074

Sensor-Based Activity Recognition

Chen, L., Hoey, J., Nugent, C. D., Cook, D. J., & Yu, Z. (2012) · IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews)

Context-Aware Activity Recognition SystemsHuman Pose and Action Recognition

Cited by 1,074

MISA: Modality-Invariant and -Specific Representations for Multimodal Sentiment Analysis

Hazarika, D., Zimmermann, R., & Poria, S. (2020) · Proceedings of the 28th ACM International Conference on Multimedia

Sentiment Analysis and Opinion MiningEmotion and Mood Recognition

Cited by 1,073

Evaluating analytic gradients on quantum hardware

Schuld, M., Bergholm, V., Gogolin, C., Izaac, J., & Killoran, N. (2019) · Physical Review A

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 1,072

Multimodal learning with transformers: A survey

Xu, P., Zhu, X., & Clifton, D. A. (2023) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Multimodal Machine Learning ApplicationsAdvanced Neural Network Applications

Cited by 1,072

Conducting Clinical Research Using Crowdsourced Convenience Samples

Chandler, J., & Shapiro, D. (2016) · Annual Review of Clinical Psychology

Mobile Crowdsensing and CrowdsourcingSurvey Methodology and Nonresponse

Cited by 1,072

The accuracy, fairness, and limits of predicting recidivism

Dressel, J., & Farid, H. (2018) · Science Advances

Ethics and Social Impacts of AICriminal Justice and Corrections Analysis

Cited by 1,071

Quantum algorithms: an overview

Montanaro, A. (2016) · npj Quantum Information

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 1,071

A Quick Review of Machine Learning Algorithms

Ray, S. (2019) · 2019 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing (COMITCon)

Data Mining and Machine Learning ApplicationsMachine Learning and Algorithms

Cited by 1,070

Observed versus latent features for knowledge base and text inference

Toutanova, K., & Chen, D. (2015) · Proceedings of the 3rd Workshop on Continuous Vector Space Models and their Compositionality

Advanced Graph Neural NetworksTopic Modeling

Cited by 1,070