Check computer science papers: citations, claims and retractions

Viewport-adaptive navigable 360-degree video delivery

Corbillon, X., Simon, G., Devlic, A., & Chakareski, J. (2017) · 2017 IEEE International Conference on Communications (ICC)

Image and Video Quality AssessmentVideo Coding and Compression Technologies

Cited by 341

Sample sizes for usability studies: Additional considerations

Lewis, J. R. (1994) · Human Factors: The Journal of the Human Factors and Ergonomics Society

Usability and User Interface DesignHuman-Automation Interaction and Safety

Cited by 341

One-Shot Visual Imitation Learning via Meta-Learning

Finn, C., Yu, T., Zhang, T., Abbeel, P., & Levine, S. (2017) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 341

Quantum annealing for industry applications: introduction and review

Yarkoni, S., Raponi, E., Bäck, T., & Schmitt, S. (2022) · Reports on Progress in Physics

Quantum Computing Algorithms and ArchitectureMetaheuristic Optimization Algorithms Research

Cited by 341

SINet: A Scale-Insensitive Convolutional Neural Network for Fast Vehicle Detection

Hu, X., Xu, X., Xiao, Y., Chen, H., He, S., Qin, J., & Heng, P.-A. (2019) · IEEE Transactions on Intelligent Transportation Systems

Advanced Neural Network ApplicationsAutonomous Vehicle Technology and Safety

Cited by 341

Benefits of Depth in Neural Networks

Telgarsky, M. (2016) · arXiv

Neural Networks and ApplicationsComplexity and Algorithms in Graphs

Cited by 341

The effects of domain knowledge on search tactic formulation

Wildemuth, B. M. (2004) · Journal of the American Society for Information Science and Technology

Information Retrieval and Search BehaviorLibrary Science and Information Literacy

Cited by 341

Graphs, Causality, and Structural Equation Models

PEARL, J. (1998) · Sociological Methods & Research

Bayesian Modeling and Causal InferenceAdvanced Causal Inference Techniques

Cited by 341

Learning Text Similarity with Siamese Recurrent Networks

Neculoiu, P., Versteegh, M., & Rotaru, M. (2016) · Proceedings of the 1st Workshop on Representation Learning for NLP

Topic ModelingData Quality and Management

Cited by 341

Qualitatively characterizing neural network optimization problems

Goodfellow, I. J., Vinyals, O., & Saxe, A. M. (2014) · arXiv

Stochastic Gradient Optimization TechniquesNeural Networks and Applications

Cited by 341

Deep Fuzzy Hashing Network for Efficient Image Retrieval

Lu, H., Zhang, M., Xu, X., Li, Y., & Shen, H. T. (2021) · IEEE Transactions on Fuzzy Systems

Advanced Image and Video Retrieval TechniquesImage Retrieval and Classification Techniques

Cited by 340

Efficient Greedy Learning of Gaussian Mixture Models

Verbeek, J. J., Vlassis, N., & Kröse, B. (2003) · Neural Computation

Bayesian Methods and Mixture ModelsAdvanced Clustering Algorithms Research

Cited by 340

HaluEval: A Large-Scale Hallucination Evaluation Benchmark for Large Language Models

Li, J., Cheng, X., Zhao, W. X., Nie, J.-Y., & Wen, J.-R. (2023) · arXiv

Topic ModelingMisinformation and Its Impacts

Cited by 340

The dropout learning algorithm

Baldi, P., & Sadowski, P. (2014) · Artificial Intelligence

Neural Networks and ApplicationsStochastic Gradient Optimization Techniques

Cited by 340

When not to trust language models: Investigating effectiveness of parametric and non-parametric memories

Mallen, A., Asai, A., Zhong, V., Das, R., Khashabi, D., & Hajishirzi, H. (2023) · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 340

Internet Key Exchange Protocol Version 2 (IKEv2)

Kaufman, C., Hoffman, P., Nir, Y., Eronen, P., & Kivinen, T. (2014)

Advanced Authentication Protocols SecurityIPv6, Mobility, Handover, Networks, Security

Cited by 340

Data Augmentation for Brain-Tumor Segmentation: A Review

Nalepa, J., Marcinkiewicz, M., & Kawulok, M. (2019) · Frontiers in Computational Neuroscience

Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques

Cited by 340

NFV and SDN—Key Technology Enablers for 5G Networks

Yousaf, F. Z., Bredel, M., Schaller, S., & Schneider, F. (2017) · IEEE Journal on Selected Areas in Communications

Software-Defined Networks and 5GAdvanced Optical Network Technologies

Cited by 340

Visual Importance Pooling for Image Quality Assessment

Moorthy, A. K., & Bovik, A. C. (2009) · IEEE Journal of Selected Topics in Signal Processing

Image and Video Quality AssessmentImage Retrieval and Classification Techniques

Cited by 340

Distributed deep learning networks among institutions for medical imaging

Chang, K., Balachandar, N., Lam, C., Yi, D., Brown, J., Beers, A., Rosen, B., Rubin, D. L., & Kalpathy-Cramer, J. (2018) · Journal of the American Medical Informatics Association

Privacy-Preserving Technologies in DataArtificial Intelligence in Healthcare and Education

Cited by 340

The debate over understanding in AI’s large language models

Mitchell, M., & Krakauer, D. C. (2023) · Proceedings of the National Academy of Sciences

Topic ModelingPhilosophy and Theoretical Science

Cited by 340

Semantic Drift Compensation for Class-Incremental Learning

Yu, L., Twardowski, B., Liu, X., Herranz, L., Wang, K., Cheng, Y., Jui, S., & van de Weijer, J. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 340

Practical elimination of near-duplicates from web video search

Wu, X., Hauptmann, A. G., & Ngo, C.-W. (2007) · Proceedings of the 15th ACM international conference on Multimedia

Video Analysis and SummarizationAdvanced Image and Video Retrieval Techniques

Cited by 340

HoloGAN: Unsupervised Learning of 3D Representations From Natural Images

Nguyen-Phuoc, T., Li, C., Theis, L., Richardt, C., & Yang, Y. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV)

Generative Adversarial Networks and Image Synthesis3D Shape Modeling and Analysis

Cited by 340