Interpretable convolutional neural networks via feedforward design CCJ Kuo, M Zhang, S Li, J Duan, Y Chen Journal of Visual Communication and Image Representation 60, 346-359, 2019 | 172 | 2019 |
On data-driven saak transform CCJ Kuo, Y Chen Journal of Visual Communication and Image Representation 50, 237-246, 2018 | 96 | 2018 |
Pixelhop++: A small successive-subspace-learning-based (ssl-based) model for image classification Y Chen, M Rouhsedaghat, S You, R Rao, CCJ Kuo 2020 IEEE International Conference on Image Processing (ICIP), 3294-3298, 2020 | 75 | 2020 |
A deep learning approach to drone monitoring Y Chen, P Aggarwal, J Choi, CCJ Kuo 2017 Asia-Pacific Signal and Information Processing Association Annual …, 2017 | 60 | 2017 |
Pixelhop: A successive subspace learning (ssl) method for object recognition Y Chen, CCJ Kuo Journal of Visual Communication and Image Representation 70, 102749, 2020 | 59 | 2020 |
Towards visible and thermal drone monitoring with convolutional neural networks Y Wang, Y Chen, J Choi, CCJ Kuo APSIPA Transactions on Signal and Information Processing 8, e5, 2019 | 41 | 2019 |
A saak transform approach to efficient, scalable and robust handwritten digits recognition Y Chen, Z Xu, S Cai, Y Lang, CCJ Kuo 2018 Picture Coding Symposium (PCS), 174-178, 2018 | 39 | 2018 |
Defense against adversarial attacks with saak transform S Song, Y Chen, NM Cheung, CCJ Kuo arXiv preprint arXiv:1808.01785, 2018 | 28 | 2018 |
Analysis on gradient propagation in batch normalized residual networks A Panigrahi, Y Chen, CCJ Kuo arXiv preprint arXiv:1812.00342, 2018 | 16 | 2018 |
Ensembles of feedforward-designed convolutional neural networks Y Chen, Y Yang, W Wang, CCJ Kuo 2019 IEEE International Conference on Image Processing (ICIP), 3796-3800, 2019 | 13 | 2019 |
An interpretable generative model for handwritten digits synthesis Y Zhu, S Suri, P Kulkarni, Y Chen, J Duan, CCJ Kuo 2019 IEEE International Conference on Image Processing (ICIP), 1910-1914, 2019 | 11 | 2019 |
Age/gender classification with whole-component convolutional neural networks (WC-CNN) CT Huang, Y Chen, R Lin, CCJ Kuo 2017 Asia-Pacific Signal and Information Processing Association Annual …, 2017 | 11 | 2017 |
Semi-supervised learning via feedforward-designed convolutional neural networks Y Chen, Y Yang, M Zhang, CCJ Kuo 2019 IEEE International Conference on Image Processing (ICIP), 365-369, 2019 | 10 | 2019 |
Unsupervised video object segmentation with distractor-aware online adaptation Y Wang, J Choi, Y Chen, S Li, Q Huang, K Zhang, MS Lee, CCJ Kuo Journal of Visual Communication and Image Representation 74, 102953, 2021 | 8 | 2021 |
Understanding convolutional neural networks via discriminant feature analysis H Xu, Y Chen, R Lin, CCJ Kuo APSIPA Transactions on Signal and Information Processing 7, e20, 2018 | 6 | 2018 |
Exploring confusing scene classes for the places dataset: Insights and solutions C Chen, S Li, X Fu, Y Ren, Y Chen, CCJ Kuo 2017 Asia-Pacific Signal and Information Processing Association Annual …, 2017 | 6 | 2017 |
Point cloud attribute compression via successive subspace graph transform Y Chen, Y Shao, J Wang, G Li, CCJ Kuo 2020 IEEE International Conference on Visual Communications and Image …, 2020 | 5 | 2020 |
Enhancing cnn incremental learning capability with an expanded network S Cai, Z Xu, Z Huang, Y Chen, CCJ Kuo 2018 IEEE International Conference on Multimedia and Expo (ICME), 1-6, 2018 | 4 | 2018 |
PixelHop: A successive subspace learning (SSL) method for object classification Y Chen, CCJ Kuo arXiv preprint arXiv:1909.08190, 2019 | 3 | 2019 |
Understanding CNN via deep features analysis H Xu, Y Chen, R Lin, CCJ Kuo 2017 Asia-Pacific Signal and Information Processing Association Annual …, 2017 | 3 | 2017 |