Check computer science papers: citations, claims and retractions

A Bag-of-Features Framework to Classify Time Series

Baydogan, M. G., Runger, G., & Tuv, E. (2013) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Time Series Analysis and ForecastingImage Retrieval and Classification Techniques

Cited by 361

Do GANs leave artificial fingerprints?

Marra, F., Gragnaniello, D., Verdoliva, L., & Poggi, G. (2019) · 2019 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR)

Digital Media Forensic DetectionGenerative Adversarial Networks and Image Synthesis

Cited by 361

An artificial neural network to estimate physical activity energy expenditure and identify physical activity type from an accelerometer

Staudenmayer, J., Pober, D., Crouter, S., Bassett, D., & Freedson, P. (2009) · Journal of Applied Physiology

Context-Aware Activity Recognition SystemsPhysical Activity and Health

Cited by 361

A secure system for pervasive social network-based healthcare

Zhang, J., Xue, N., & Huang, X. (2016) · IEEE Access

Advanced Authentication Protocols SecurityWireless Body Area Networks

Cited by 361

Crosslingual Generalization through Multitask Finetuning

Muennighoff, N., Wang, T., Sutawika, L., Roberts, A., Biderman, S., Le Scao, T., Bari, M. S., Shen, S., Yong, Z. X., Schoelkopf, H., et al. (2023) · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 361

Categorical and dimensional affect analysis in continuous input: Current trends and future directions

Gunes, H., & Schuller, B. (2013) · Image and Vision Computing

Emotion and Mood RecognitionSentiment Analysis and Opinion Mining

Cited by 360

A systematic review on trends in using Moodle for teaching and learning

Gamage, S. H. P. W., Ayres, J. R., & Behrend, M. B. (2022) · International Journal of STEM Education

Educational Technology and E-LearningOnline and Blended Learning

Cited by 360

Nonconvex Optimization Meets Low-Rank Matrix Factorization: An Overview

Chi, Y., Lu, Y. M., & Chen, Y. (2019) · IEEE Transactions on Signal Processing

Sparse and Compressive Sensing TechniquesStochastic Gradient Optimization Techniques

Cited by 360

Fast crash recovery in RAMCloud

Ongaro, D., Rumble, S. M., Stutsman, R., Ousterhout, J., & Rosenblum, M. (2011) · Proceedings of the Twenty-Third ACM Symposium on Operating Systems Principles

Advanced Data Storage TechnologiesDistributed systems and fault tolerance

Cited by 360

Pyserini: A Python toolkit for reproducible information retrieval research with sparse and dense representations

Lin, J., Ma, X., Lin, S.-C., Yang, J.-H., Pradeep, R., & Nogueira, R. (2021) · Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval

Information Retrieval and Search BehaviorTopic Modeling

Cited by 360

Artificial intelligence and business strategy towards digital transformation: A research agenda

Kitsios, F., & Kamariotou, M. (2021) · Sustainability

Artificial Intelligence ApplicationsInformation Technology Governance and Strategy

Cited by 360

A quantum-inspired classical algorithm for recommendation systems

Tang, E. (2019) · Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing

Quantum Computing Algorithms and ArchitectureRecommender Systems and Techniques

Cited by 360

PPSF: a privacy-preserving and secure framework using blockchain-based machine-learning for IoT-driven smart cities

Kumar, P., Kumar, R., Srivastava, G., Gupta, G. P., Tripathi, R., Gadekallu, T. R., & Xiong, N. N. (2021) · IEEE Transactions on Network Science and Engineering

Blockchain Technology Applications and SecurityIoT and Edge/Fog Computing

Cited by 360

A-ViT: Adaptive Tokens for Efficient Vision Transformer

Yin, H., Vahdat, A., Alvarez, J. M., Mallya, A., Kautz, J., & Molchanov, P. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 360

Applications of Artificial Intelligence in Machine Learning: Review and Prospect

Das, S., Dey, A., Pal, A., & Roy, N. (2015) · International Journal of Computer Applications

Artificial Intelligence ApplicationsMachine Learning and Algorithms

Cited by 360

SearchQA: A New Q&A Dataset Augmented with Context from a Search Engine

Dunn, M., Sagun, L., Higgins, M., Guney, V. U., Cirik, V., & Cho, K. (2017) · arXiv

Topic ModelingInformation Retrieval and Search Behavior

Cited by 359

A Quantum Algorithm for Finding the Minimum

Durr, C., & Hoyer, P. (1996) · arXiv

Quantum Computing Algorithms and ArchitectureComplexity and Algorithms in Graphs

Cited by 359

Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents

Machado, M. C., Bellemare, M. G., Talvitie, E., Veness, J., Hausknecht, M., & Bowling, M. (2018) · Journal of Artificial Intelligence Research

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 359

Algorithmic governance

Katzenbach, C., & Ulbricht, L. (2019) · Internet Policy Review

Ethics and Social Impacts of AILegal and Labor Studies

Cited by 359

Human-Aware Motion Deblurring

Shen, Z., Wang, W., Lu, X., Shen, J., Ling, H., Xu, T., & Shao, L. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV)

Advanced Image Processing TechniquesImage Enhancement Techniques

Cited by 359

AFlow: Automating Agentic Workflow Generation

Zhang, J., Xiang, J., Yu, Z., Teng, F., Chen, X., Chen, J., Zhuge, M., Cheng, X., Hong, S., Wang, J., et al. (2024) · arXiv

AI-based Problem Solving and PlanningArtificial Intelligence Applications

Cited by 359

Objective video quality assessment

Furht, B., & Marques, O. (2003) · Handbook of Video Databases

Image and Video Quality AssessmentVideo Coding and Compression Technologies

Cited by 359

Intrusion Detection for IoT Based on Improved Genetic Algorithm and Deep Belief Network

Zhang, Y., Li, P., & Wang, X. (2019) · IEEE Access

Network Security and Intrusion DetectionNetwork Packet Processing and Optimization

Cited by 359

CycleGAN-VC: Non-parallel Voice Conversion Using Cycle-Consistent Adversarial Networks

Kaneko, T., & Kameoka, H. (2018) · 2018 26th European Signal Processing Conference (EUSIPCO)

Speech Recognition and SynthesisSpeech and Audio Processing

Cited by 358