Check computer science papers: citations, claims and retractions

Is Augmented Reality Technology an Effective Tool for E-commerce? An Interactivity and Vividness Perspective

Yim, M. Y.-C., Chu, S.-C., & Sauer, P. L. (2017) · Journal of Interactive Marketing

Augmented Reality ApplicationsConsumer Retail Behavior Studies

Cited by 1,142

Using Mechanical Turk to Study Clinical Populations

Shapiro, D. N., Chandler, J., & Mueller, P. A. (2013) · Clinical Psychological Science

Mobile Crowdsensing and CrowdsourcingSurvey Methodology and Nonresponse

Cited by 1,139

Deep multimodal learning: a survey on recent advances and trends

Ramachandram, D., & Taylor, G. W. (2017) · IEEE Signal Processing Magazine

Multimodal Machine Learning ApplicationsAdvanced Image Fusion Techniques

Cited by 1,139

Multivariate LSTM-FCNs for time series classification

Karim, F., Majumdar, S., Darabi, H., & Harford, S. (2019) · Neural Networks

Time Series Analysis and ForecastingContext-Aware Activity Recognition Systems

Cited by 1,138

Challenges of open innovation: the paradox of firm investment in open-source software

West, J., & Gallagher, S. (2006) · R and D Management

Open Source Software InnovationsInnovation and Knowledge Management

Cited by 1,136

DREAMER: A Database for Emotion Recognition Through EEG and ECG Signals From Wireless Low-cost Off-the-Shelf Devices

Katsigiannis, S., & Ramzan, N. (2018) · IEEE Journal of Biomedical and Health Informatics

Emotion and Mood RecognitionEEG and Brain-Computer Interfaces

Cited by 1,135

Comparison and evaluation of methods for liver segmentation from CT datasets

Heimann, T., van Ginneken, B., Styner, M. A., Arzhaeva, Y., Aurich, V., Bauer, C., Beck, A., Becker, C., Beichel, R., Bekes, G., et al. (2009) · IEEE Transactions on Medical Imaging

Medical Image Segmentation TechniquesMedical Imaging and Analysis

Cited by 1,135

An experimental unification of reservoir computing methods

Verstraeten, D., Schrauwen, B., D’Haene, M., & Stroobandt, D. (2007) · Neural Networks

Neural Networks and Reservoir ComputingAdvanced Memory and Neural Computing

Cited by 1,135

Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training

Lin, Y., Han, S., Mao, H., Wang, Y., & Dally, W. J. (2017) · arXiv

Stochastic Gradient Optimization TechniquesMachine Learning and Data Classification

Cited by 1,134

Structural-RNN: Deep Learning on Spatio-Temporal Graphs

Jain, A., Zamir, A. R., Savarese, S., & Saxena, A. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Graph Neural NetworksHuman Pose and Action Recognition

Cited by 1,133

Machine Learning and Deep Learning Methods for Intrusion Detection Systems: A Survey

Liu, H., & Lang, B. (2019) · Applied Sciences

Network Security and Intrusion DetectionNetwork Packet Processing and Optimization

Cited by 1,133

Blockchain technology in healthcare: a systematic review

Agbo, C. C., Mahmoud, Q. H., & Eklund, J. M. (2019) · Healthcare

Blockchain Technology Applications and SecurityBlockchain Technology in Education and Learning

Cited by 1,131

What can machine learning do? Workforce implications

Brynjolfsson, E., & Mitchell, T. (2017) · Science

Ethics and Social Impacts of AILabor market dynamics and wage inequality

Cited by 1,131

MaskGAN: Towards Diverse and Interactive Facial Image Manipulation

Lee, C.-H., Liu, Z., Wu, L., & Luo, P. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Generative Adversarial Networks and Image SynthesisFace recognition and analysis

Cited by 1,130

Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates

Yin, D., Chen, Y., Ramchandran, K., & Bartlett, P. (2018) · arXiv

Stochastic Gradient Optimization TechniquesPrivacy-Preserving Technologies in Data

Cited by 1,130

ScribbleSup: Scribble-Supervised Convolutional Networks for Semantic Segmentation

Lin, D., Dai, J., Jia, J., He, K., & Sun, J. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsMedical Image Segmentation Techniques

Cited by 1,129

3D Bounding Box Estimation Using Deep Learning and Geometry

Mousavian, A., Anguelov, D., Flynn, J., & Kosecka, J. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 1,129

A Survey of Predictive Modeling on Imbalanced Domains

Branco, P., Torgo, L., & Ribeiro, R. P. (2017) · ACM Computing Surveys

Imbalanced Data Classification TechniquesCustomer churn and segmentation

Cited by 1,129

Deep learning for brain MRI segmentation: state of the art and future directions

Akkus, Z., Galimzianova, A., Hoogi, A., Rubin, D. L., & Erickson, B. J. (2017) · Journal of Digital Imaging

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 1,129

Dynamic Few-Shot Visual Learning Without Forgetting

Gidaris, S., & Komodakis, N. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 1,128

Taskonomy: Disentangling Task Transfer Learning

Zamir, A. R., Sax, A., Shen, W., Guibas, L., Malik, J., & Savarese, S. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 1,128

The UCR time series archive

Dau, H. A., Bagnall, A., Kamgar, K., Yeh, C.-C. M., Zhu, Y., Gharghabi, S., Ratanamahatana, C. A., & Keogh, E. (2019) · IEEE/CAA Journal of Automatica Sinica

Time Series Analysis and ForecastingData Mining and Machine Learning Applications

Cited by 1,128

A survey on ambient-assisted living tools for older adults

Rashidi, P., & Mihailidis, A. (2013) · IEEE Journal of Biomedical and Health Informatics

Context-Aware Activity Recognition SystemsTechnology Use by Older Adults

Cited by 1,128

Sigmoid Loss for Language Image Pre-Training

Zhai, X., Mustafa, B., Kolesnikov, A., & Beyer, L. (2023) · 2023 IEEE/CVF International Conference on Computer Vision (ICCV)

Multimodal Machine Learning ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 1,127