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publications

CNN-based multilayer spatial–spectral feature fusion and sample augmentation with local and nonlocal constraints for hyperspectral image classification

Published in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2019

JCR Q2

Recommended citation: Feng, J., Chen, J., Liu, L., Cao, X., Zhang, X., Jiao, L., & Yu, T. (2019). CNN-based multilayer spatial–spectral feature fusion and sample augmentation with local and nonlocal constraints for hyperspectral image classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12(4), 1299-1313.
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Joint multilayer spatial-spectral classification of hyperspectral images based on CNN and ConvLSTM

Published in IGARSS 2019-2019 IEEE International Geoscience and Remote Sensing Symposium, 2019

Recommended citation: Feng, J., Wu, X., Chen, J., Zhang, X., Tang, X., & Li, D. (2019, July). Joint multilayer spatial-spectral classification of hyperspectral images based on CNN and ConvLSTM. In IGARSS 2019-2019 IEEE International Geoscience and Remote Sensing Symposium (pp. 588-591). IEEE.
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Hyperspectral band selection based on ternary weight convolutional neural network

Published in IGARSS 2019-2019 IEEE International Geoscience and Remote Sensing Symposium, 2019

Recommended citation: Feng, J., Li, D., Chen, J., Zhang, X., Tang, X., & Wu, X. (2019, July). Hyperspectral band selection based on ternary weight convolutional neural network. In IGARSS 2019-2019 IEEE International Geoscience and Remote Sensing Symposium (pp. 3804-3807). IEEE.
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Generative adversarial networks based on collaborative learning and attention mechanism for hyperspectral image classification

Published in Remote Sensing, 2020

JCR Q2

Recommended citation: Feng, J., Feng, X., Chen, J., Cao, X., Zhang, X., Jiao, L., & Yu, T. (2020). Generative adversarial networks based on collaborative learning and attention mechanism for hyperspectral image classification. Remote Sensing, 12(7), 1149.
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Convolutional neural network based on bandwise-independent convolution and hard thresholding for hyperspectral band selection

Published in IEEE transactions on cybernetics, 2020

JCR Q1

Recommended citation: Feng, J., Chen, J., Sun, Q., Shang, R., Cao, X., Zhang, X., & Jiao, L. (2020). Convolutional neural network based on bandwise-independent convolution and hard thresholding for hyperspectral band selection. IEEE transactions on cybernetics, 51(9), 4414-4428.
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Dual-graph convolutional network based on band attention and sparse constraint for hyperspectral band selection

Published in Knowledge-Based Systems, 2021

JCR Q1

Recommended citation: Feng, J., Ye, Z., Liu, S., Zhang, X., Chen, J., Shang, R., & Jiao, L. (2021). Dual-graph convolutional network based on band attention and sparse constraint for hyperspectral band selection. Knowledge-Based Systems, 231, 107428.
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Toward Motion Robustness: A masked attention regularization framework in remote photoplethysmography

Published in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Recommended citation: Zhao, P., Sun, Q., Tian, X., Yang, Y., Tao, S., Cheng, J., & Chen, J. (2024). Toward Motion Robustness: A masked attention regularization framework in remote photoplethysmography. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 7829-7838).
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teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

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Teaching experience 2

Workshop, University 1, Department, 2015