Check computer science papers: citations, claims and retractions

When Does Contrastive Visual Representation Learning Work?

Cole, E., Yang, X., Wilber, K., Aodha, O. M., & Belongie, S. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 105

The Racist Algorithm?

Chander, A. (2017) · Michigan Law Review

Ethics and Social Impacts of AIDigitalization, Law, and Regulation

Cited by 105

Multiclass Classification for the Differential Diagnosis on the ADHD Subtypes Using Recursive Feature Elimination and Hierarchical Extreme Learning Machine: Structural MRI Study

Qureshi, M. N. I., Min, B., Jo, H. J., & Lee, B. (2016) · PLOS ONE

Machine Learning and ELMAttention Deficit Hyperactivity Disorder

Cited by 105

Information flow control for secure cloud computing

Bacon, J., Eyers, D., Pasquier, T. F. J.-M., Singh, J., Papagiannis, I., & Pietzuch, P. (2014) · IEEE Transactions on Network and Service Management

Cloud Data Security SolutionsSecurity and Verification in Computing

Cited by 105

Accelerating Transformer-based Deep Learning Models on FPGAs using Column Balanced Block Pruning

Peng, H., Huang, S., Geng, T., Li, A., Jiang, W., Liu, H., Wang, S., & Ding, C. (2021) · 2021 22nd International Symposium on Quality Electronic Design (ISQED)

Advanced Neural Network ApplicationsEmbedded Systems Design Techniques

Cited by 105

An overview of adaptive e-learning systems

Ennouamani, S., & Mahani, Z. (2017) · 2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS)

Intelligent Tutoring Systems and Adaptive LearningEducational Technology and E-Learning

Cited by 105

A qualitative research framework for the design of user-centered displays of explanations for machine learning model predictions in healthcare

Barda, A. J., Horvat, C. M., & Hochheiser, H. (2020) · BMC Medical Informatics and Decision Making

Explainable Artificial Intelligence (XAI)Machine Learning in Healthcare

Cited by 105

Development and Validation of a Deep Learning Algorithm for Mortality Prediction in Selecting Patients With Dementia for Earlier Palliative Care Interventions

Wang, L., Sha, L., Lakin, J. R., Bynum, J., Bates, D. W., Hong, P., & Zhou, L. (2019) · JAMA Network Open

Machine Learning in HealthcarePalliative Care and End-of-Life Issues

Cited by 105

Embedded Intelligence on FPGA: Survey, Applications and Challenges

Seng, K. P., Lee, P. J., & Ang, L. M. (2021) · Electronics

Embedded Systems Design TechniquesEmbedded Systems and FPGA Applications

Cited by 105

Computational Work and Time on Finite Machines

Savage, J. E. (1972) · Journal of the ACM

Computability, Logic, AI AlgorithmsAlgorithms and Data Compression

Cited by 105

Deep learning generalizes because the parameter-function map is biased towards simple functions

Valle-Pérez, G., Camargo, C. Q., & Louis, A. A. (2018) · arXiv

Stochastic Gradient Optimization TechniquesMachine Learning and Algorithms

Cited by 105

Exploring the Challenges of Artificial Intelligence in Data Integrity and its Influence on Social Dynamics

Oladoyinbo, T. O., Olabanji, S. O., Olaniyi, O. O., Adebiyi, O. O., Okunleye, O. J., & Alao, A. I. (2024) · Asian Journal of Advanced Research and Reports

Ethics and Social Impacts of AIDigitalization, Law, and Regulation

Cited by 105

Language Model Behavior: A Comprehensive Survey

Chang, T. A., & Bergen, B. K. (2024) · Computational Linguistics

Topic ModelingNatural Language Processing Techniques

Cited by 105

A Study of Social Engineering in Online Frauds

Atkins, B., & Huang, W. (2013) · Open Journal of Social Sciences

Spam and Phishing DetectionCybercrime and Law Enforcement Studies

Cited by 105

Computation Offloading Method Using Stochastic Games for Software-Defined-Network-Based Multiagent Mobile Edge Computing

Wu, G., Wang, H., Zhang, H., Zhao, Y., Yu, S., & Shen, S. (2023) · IEEE Internet of Things Journal

IoT and Edge/Fog ComputingSoftware-Defined Networks and 5G

Cited by 105

Preserving Privacy in the Internet of Connected Vehicles

Ghane, S., Jolfaei, A., Kulik, L., Ramamohanarao, K., & Puthal, D. (2021) · IEEE Transactions on Intelligent Transportation Systems

Privacy-Preserving Technologies in DataVehicular Ad Hoc Networks (VANETs)

Cited by 105

Smart Surveillance as an Edge Network Service: From Harr-Cascade, SVM to a Lightweight CNN

Nikouei, S. Y., Chen, Y., Song, S., Xu, R., Choi, B.-Y., & Faughnan, T. (2018) · 2018 IEEE 4th International Conference on Collaboration and Internet Computing (CIC)

Video Surveillance and Tracking MethodsAdvanced Neural Network Applications

Cited by 105

Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets

Blattmann, A., Dockhorn, T., Kulal, S., Mendelevitch, D., Kilian, M., Lorenz, D., Levi, Y., English, Z., Voleti, V., Letts, A., et al. (2023) · arXiv

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 105

Face Generation and Editing With StyleGAN: A Survey

Melnik, A., Miasayedzenkau, M., Makaravets, D., Pirshtuk, D., Akbulut, E., Holzmann, D., Renusch, T., Reichert, G., & Ritter, H. (2024) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Generative Adversarial Networks and Image SynthesisFace recognition and analysis

Cited by 105

Mitigating Realistic Noise in Practical Noisy Intermediate-Scale Quantum Devices

Sun, J., Yuan, X., Tsunoda, T., Vedral, V., Benjamin, S. C., & Endo, S. (2021) · Physical Review Applied

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 105

Are We Hungry for 3D LiDAR Data for Semantic Segmentation? A Survey of Datasets and Methods

Gao, B., Pan, Y., Li, C., Geng, S., & Zhao, H. (2022) · IEEE Transactions on Intelligent Transportation Systems

Advanced Neural Network Applications3D Shape Modeling and Analysis

Cited by 105

TEACh: Task-Driven Embodied Agents That Chat

Padmakumar, A., Thomason, J., Shrivastava, A., Lange, P., Narayan-Chen, A., Gella, S., Piramuthu, R., Tur, G., & Hakkani-Tur, D. (2022) · Proceedings of the AAAI Conference on Artificial Intelligence

Speech and dialogue systemsSocial Robot Interaction and HRI

Cited by 105

Development and evaluation of an automated machine learning algorithm for in-hospital mortality risk adjustment among critical care patients.

Delahanty, R. J., Kaufman, D., & Jones, S. S. (2018) · Critical Care Medicine

Machine Learning in HealthcareSepsis Diagnosis and Treatment

Cited by 105

A sentiment analysis model for hotel reviews based on supervised learning

Shi, H.-X., & Li, X.-J. (2011) · 2011 International Conference on Machine Learning and Cybernetics

Sentiment Analysis and Opinion MiningText and Document Classification Technologies

Cited by 105