Check computer science papers: citations, claims and retractions

Mobile-assisted language learning: A Duolingo case study

Loewen, S., Crowther, D., Isbell, D. R., Kim, K. M., Maloney, J., Miller, Z. F., & Rawal, H. (2019) · ReCALL

Mobile Learning in EducationEFL/ESL Teaching and Learning

Cited by 368

Applications of Explainable Artificial Intelligence in Diagnosis and Surgery

Zhang, Y., Weng, Y., & Lund, J. (2022) · Diagnostics

Explainable Artificial Intelligence (XAI)Artificial Intelligence in Healthcare and Education

Cited by 368

M2TR: Multi-modal Multi-scale Transformers for Deepfake Detection

Wang, J., Wu, Z., Ouyang, W., Han, X., Chen, J., Jiang, Y.-G., & Li, S.-N. (2022) · Proceedings of the 2022 International Conference on Multimedia Retrieval

Digital Media Forensic DetectionGenerative Adversarial Networks and Image Synthesis

Cited by 368

Video Quality Assessment by Reduced Reference Spatio-Temporal Entropic Differencing

Soundararajan, R., & Bovik, A. C. (2013) · IEEE Transactions on Circuits and Systems for Video Technology

Image and Video Quality AssessmentImage Retrieval and Classification Techniques

Cited by 368

Online Learning for Offloading and Autoscaling in Energy Harvesting Mobile Edge Computing

Xu, J., Chen, L., & Ren, S. (2017) · IEEE Transactions on Cognitive Communications and Networking

IoT and Edge/Fog ComputingEnergy Efficiency in Computing

Cited by 368

Human Activity Recognition Using Inertial, Physiological and Environmental Sensors: A Comprehensive Survey

Demrozi, F., Pravadelli, G., Bihorac, A., & Rashidi, P. (2020) · IEEE Access

Context-Aware Activity Recognition SystemsGait Recognition and Analysis

Cited by 368

DETRs Beat YOLOs on Real-time Object Detection

Zhao, Y., Lv, W., Xu, S., Wei, J., Wang, G., Dang, Q., Liu, Y., & Chen, J. (2023) · arXiv

Advanced Neural Network ApplicationsVisual Attention and Saliency Detection

Cited by 368

Deep learning with convolutional neural network in radiology

Yasaka, K., Akai, H., Kunimatsu, A., Kiryu, S., & Abe, O. (2018) · Japanese Journal of Radiology

AI in cancer detectionArtificial Intelligence in Healthcare and Education

Cited by 368

One Fits All: Power General Time Series Analysis by Pretrained LM

Zhou, T., Niu, P., Wang, X., Sun, L., & Jin, R. (2023) · Advances in Neural Information Processing Systems 36

Time Series Analysis and ForecastingEnergy Load and Power Forecasting

Cited by 367

NoScope: optimizing neural network queries over video at scale

Kang, D., Emmons, J., Abuzaid, F., Bailis, P., & Zaharia, M. (2017) · Proceedings of the VLDB Endowment

Advanced Neural Network ApplicationsVideo Surveillance and Tracking Methods

Cited by 367

When large language models meet personalization: perspectives of challenges and opportunities

Chen, J., Liu, Z., Huang, X., Wu, C., Liu, Q., Jiang, G., Pu, Y., Lei, Y., Chen, X., Wang, X., et al. (2024) · World Wide Web

Recommender Systems and TechniquesInformation Retrieval and Search Behavior

Cited by 367

Edge YOLO: Real-Time Intelligent Object Detection System Based on Edge-Cloud Cooperation in Autonomous Vehicles

Liang, S., Wu, H., Zhen, L., Hua, Q., Garg, S., Kaddoum, G., Hassan, M. M., & Yu, K. (2022) · IEEE Transactions on Intelligent Transportation Systems

Advanced Neural Network ApplicationsIoT and Edge/Fog Computing

Cited by 367

EEG-based emotion classification using deep belief networks

Zheng, W.-L., Zhu, J.-Y., Peng, Y., & Lu, B.-L. (2014) · 2014 IEEE International Conference on Multimedia and Expo (ICME)

Emotion and Mood RecognitionEEG and Brain-Computer Interfaces

Cited by 367

An optimum character recognition system using decision functions

Chow, C. K. (1957) · IRE Transactions on Electronic Computers

Handwritten Text Recognition TechniquesVehicle License Plate Recognition

Cited by 367

CNP: An FPGA-based processor for Convolutional Networks

Farabet, C., Poulet, C., Han, J. Y., & LeCun, Y. (2009) · 2009 International Conference on Field Programmable Logic and Applications

Advanced Neural Network ApplicationsEmbedded Systems Design Techniques

Cited by 367

High-quality video view interpolation using a layered representation

Zitnick, C. L., Kang, S. B., Uyttendaele, M., Winder, S., & Szeliski, R. (2004) · ACM SIGGRAPH 2004 Papers

Advanced Vision and ImagingComputer Graphics and Visualization Techniques

Cited by 367

Privacy-preserving and efficient aggregation based on blockchain for power grid communications in smart communities

Guan, Z., Si, G., Zhang, X., Wu, L., Guizani, N., Du, X., & Ma, Y. (2018) · IEEE Communications Magazine

Blockchain Technology Applications and SecuritySmart Grid Security and Resilience

Cited by 367

e-SNLI: Natural language inference with natural language explanations

Camburu, O.-M., Rocktäschel, T., Lukasiewicz, T., & Blunsom, P. (2018) · arXiv

Explainable Artificial Intelligence (XAI)Topic Modeling

Cited by 367

Security for 5G and beyond

Ahmad, I., Shahabuddin, S., Kumar, T., Okwuibe, J., Gurtov, A., & Ylianttila, M. (2019) · IEEE Communications Surveys & Tutorials

Cybersecurity and Information SystemsSoftware-Defined Networks and 5G

Cited by 366

Studying the effect of AI Code Generators on Supporting Novice Learners in Introductory Programming

Kazemitabaar, M., Chow, J., Ma, C. K. T., Ericson, B. J., Weintrop, D., & Grossman, T. (2023) · Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems

Teaching and Learning ProgrammingSoftware Engineering Research

Cited by 366

Understanding image representations by measuring their equivariance and equivalence

Lenc, K., & Vedaldi, A. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 366

Finding low-energy conformations of lattice protein models by quantum annealing

Perdomo-Ortiz, A., Dickson, N., Drew-Brook, M., Rose, G., & Aspuru-Guzik, A. (2012) · Scientific Reports

Quantum Computing Algorithms and ArchitectureProtein Structure and Dynamics

Cited by 366

Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review

Levine, S. (2018) · arXiv

Reinforcement Learning in RoboticsAdaptive Dynamic Programming Control

Cited by 366

Sparse Autoencoder-Based Feature Transfer Learning for Speech Emotion Recognition

Deng, J., Zhang, Z., Marchi, E., & Schuller, B. (2013) · 2013 Humaine Association Conference on Affective Computing and Intelligent Interaction

Emotion and Mood RecognitionSpeech Recognition and Synthesis

Cited by 366