Feng Gao 高峰

Associate Professor
School of Computer Science
Ocean Unversity of China


Publications [ Google Scholar ]

2024

  1. L. Qi, M. Yue, F. Gao*, B. Cao, J. Dong and X. Gao, "Deep Attention-Guided Spatial–Spectral Network for Hyperspectral Image Unmixing," IEEE Geoscience and Remote Sensing Letters, vol. 21, pp. 1-5, 2024. [PDF]

  2. S. Tao, Y. Li, F. Gao, H. Fan, J. Dong*, Y. Gan*, "Multi-Scale Spatial Features and Temporal Attention Mechanisms: Advancing the Accuracy of ENSO Prediction," Intelligent Marine Technology and Systems, 2024. [PDF]

2023

  1. J. Lin, F. Gao*, X. Shi, J. Dong, Q. Du, “SS-MAE: Spatial-Spectral Masked Auto-Encoder for Multi-Source Remote Sensing Image Classification,” IEEE Transactions on Geoscience and Remote Sensing, vol. 61, pp. 1-15, 2023. [PDF] [Code@Github]

  2. Y. Meng, E. Rigall, X. Chen, F. Gao*, J. Dong* and S. Chen, "Physics-Guided Generative Adversarial Networks for Sea Subsurface Temperature Prediction," IEEE Transactions on Neural Networks and Learning Systems, vol. 34, no. 7, pp. 3357-3370, 2023. [PDF] [Code@github]

  3. Y. Meng, F. Gao*, E. Rigall, R. Dong, J. Dong* and Q. Du, "Physical Knowledge-Enhanced Deep Neural Network for Sea Surface Temperature Prediction," IEEE Transactions on Geoscience and Remote Sensing, vol. 61, pp. 1-13, 2023. [PDF]

  4. M. Wang, F. Gao*, J. Dong, H. -C. Li and Q. Du, "Nearest Neighbor-Based Contrastive Learning for Hyperspectral and LiDAR Data Classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 61, pp. 1-16, 2023. [PDF] [Code@Github]

  5. L. Qi, Z. Chen, F. Gao*, J. Dong*, X. Gao and Q. Du, "Multiview Spatial-Spectral Two-Stream Network for Hyperspectral Image Unmixing," IEEE Transactions on Geoscience and Remote Sensing, vol. 61, pp. 1-16, 2023. [PDF]

  6. Y. Rao, Y. Ju, S. Wang, F. Gao, H. Fan and J. Dong*, "Learning Enriched Feature Descriptor for Image Matching and Visual Measurement," IEEE Transactions on Instrumentation and Measurement, vol. 72, pp. 1-12, 2023. [PDF] [Code@Github]

  7. H. Zhang, Z. Lin, F. Gao*, J. Dong, Q. Du and H. -C. Li, "Convolution and Attention Mixer for Synthetic Aperture Radar Image Change Detection," IEEE Geoscience and Remote Sensing Letters, vol. 20, pp. 1-5, 2023. [PDF] [Code@Github]

  8. L. Qi, X. Qin, F. Gao*, J. Dong and X. Gao, “SAWU-Net: Spatial Attention Weighted Unmixing Network for Hyperspectral Images,” IEEE Geoscience and Remote Sensing Letters, vol. 20, pp. 1-5, 2023. [PDF]

  9. H. Pan, F. Gao, J. Dong and Q. Du, "Multiscale Adaptive Fusion Network for Hyperspectral Image Denoising," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 16, pp. 3045-3059, 2023. [PDF] [Code@Github]

  10. Z. Yang, L. Qi, F. Gao and J. Lin, "Multiview Siamese Collaborative Network for Hyperspectral Image Unmixing," IGARSS 2023, pp. 5902-5905.

  11. S. Hu, Y. Hu, J. Lin, F. Gao and J. Dong, "Multi-Scale Transformer Network for Hyperspectral Image Denoising," IGARSS 2023, pp. 7328-7331.

  12. X. Shi, J. Lin, Y. Rao, Y. Sun and F. Gao, "Gated-Cross Aggregation Network for Hyperspectral and LiDAR Data Classification," IGARSS 2023, pp. 1265-1268.

  13. L. Lv, J. Lin, F. Gao, L. Qi and J. Dong, "Hyperspectral and SAR Image Classification via Recursive Feature Interactive Fusion Network," IGARSS 2023, pp. 6282-6285.

2022

  1. Y. Gan, F. Gao, J. Dong*, S. Chen, "Arbitrary-Scale Texture Generation from Coarse-Grained Control," IEEE Transactions on Image Processing, vol. 31, pp. 5841-5855, 2022. [PDF] [Code@Github]

  2. Y. Gan, X. Dong, H. Zhou, F. Gao and J. Dong*, "Learning the Precise Feature for Cluster Assignment," IEEE Transactions on Cybernetics, vol. 52, no. 8, pp. 8587-8600, 2022. [PDF]

  3. L. Qi, F. Gao*, J. Dong*, X. Gao and Q. Du, "SSCU-Net: Spatial–Spectral Collaborative Unmixing Network for Hyperspectral Images," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022. [PDF]

  4. W. -S. Hu, H. -C. Li, R. Wang, F. Gao, Q. Du and A. Plaza, "Pseudo Complex-Valued Deformable ConvLSTM Neural Network With Mutual Attention Learning for Hyperspectral Image Classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-17, 2022. [PDF]

  5. J. Wang, F. Gao*, J. Dong, Q. Du and H. Li, "Change Detection from Synthetic Aperture Radar Images via Dual Path Denoising Network," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 2667-2680, 2022. [PDF]

  6. D. Meng, F. Gao*, J. Dong, Q. Du and H. -C. Li, "Synthetic Aperture Radar Image Change Detection via Layer Attention-Based Noise-Tolerant Network," IEEE Geoscience and Remote Sensing Letters, vol. 19, 2022. [PDF] [Code@Github]

  7. J. Wang, F. Gao*, J. Dong, S. Zhang and Q. Du, "Change Detection From Synthetic Aperture Radar Images via Graph-Based Knowledge Supplement Network," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 1823-1836, 2022. [PDF] [Code@github]

  8. X. Qu, F. Gao*, J. Dong, Q. Du and H. -C. Li, "Change Detection in Synthetic Aperture Radar Images Using a Dual-Domain Network," IEEE Geoscience and Remote Sensing Letters, vol. 19, pp. 1-5, 2022, Art no. 4013405. [PDF] [Code@github]

  9. T. Zhang, F. Gao*, J. Dong and Q. Du, "Remote Sensing Image Translation via Style-Based Recalibration Module and Improved Style Discriminator," IEEE Geoscience and Remote Sensing Letters, vol. 19, pp. 1-5, 2022, Art no. 8009805. [PDF] [Code@github]

  10. X. Li, F. Gao, J. Dong and L. Qi, "Change Detection in Sar Images Based on A Multi-Scale Attention Convolution Network," IGARSS 2022, pp. 3219-3222.

  11. M. Zhang, F. Gao, J. Dong and L. Qi, "Multi-Scale Feature Fusion for Hyperspectral and Lidar Data Joint Classification," IGARSS 2022, pp. 2856-2859.

  12. Z. Gong, F. Gao, J. Dong and L. Qi, "Hyperspectral Image Denoising Based on Parallel Cross-Fusion Network," IGARSS 2022, pp. 1528-1531.

2021

  1. J. Wang, F. Gao*, J. Dong and Q. Du, "Adaptive DropBlock-Enhanced Generative Adversarial Networks for Hyperspectral Image Classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 6, pp. 5040-5053, 2021. [PDF] [Code@github]

  2. Y. Gao, F. Gao*, J. Dong, Q. Du and H. -C. Li, "Synthetic Aperture Radar Image Change Detection via Siamese Adaptive Fusion Network," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 10748-10760, 2021. [PDF] [Code@github]

  3. Y. Gao, F. Gao*, J. Dong and H. -C. Li, "SAR Image Change Detection Based on Multiscale Capsule Network," IEEE Geoscience and Remote Sensing Letters, vol. 18, no. 3, pp. 484-488, 2021. [PDF] [Code@github]

  4. W. Liu, F. Gao and J. Dong, "Disentangled Non-Local Network for Hyperspectral and LiDAR Data Classification," IGARSS 2021, pp. 2397-2400.

  5. M. Feng, F. Gao, J. Fang and J. Dong, "Hyperspectral and Lidar Data Classification Based on Linear Self-Attention," IGARSS 2021, pp. 2401-2404.

Former

  1. Y. Gao, F. Gao*, J. Dong and S. Wang, "Change Detection From Synthetic Aperture Radar Images Based on Channel Weighting-Based Deep Cascade Network," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 12, no. 11, pp. 4517-4529, Nov. 2019. [PDF] [Code@Github]

  2. Y. Gao, F. Gao*, J. Dong and S. Wang, "Transferred Deep Learning for Sea Ice Change Detection From Synthetic Aperture Radar Images," IEEE Geoscience and Remote Sensing Letters, vol. 16, no. 10, pp. 1655-1659, Oct. 2019. [PDF] [Code@Github]

  3. F. Gao, X. Wang, Y. Gao, J. Dong* and S. Wang, "Sea Ice Change Detection in SAR Images Based on Convolutional-Wavelet Neural Networks," IEEE Geoscience and Remote Sensing Letters, vol. 16, no. 8, pp. 1240-1244, 2019. [PDF] [Code@Github]

  4. F. Gao, Q. Wang, J. Dong*, S. Wang, "Spectral and spatial classification of hyperspectral images based on random multi-graphs," Remote Sensing, 2018. [PDF] [Code@github]

  5. F. Gao, X. Wang, J. Dong*, S. Wang, "SAR image change detection based on frequency domain analysis and random multi-graphs," Journal of Applied Remote Sensing, 2018. [PDF] [Code@github]

  6. F. Gao, J. Dong*, B. Li, Q. Xu, C. Xie, "Change detection from synthetic aperture radar images based on neighborhood-based ratio and extreme learning machine," Journal of Applied Remote Sensing, 2016. [PDF] [Code@github]

  7. F. Gao, J. Dong*, B. Li and Q. Xu, "Automatic Change Detection in Synthetic Aperture Radar Images Based on PCANet," IEEE Geoscience and Remote Sensing Letters, vol. 13, no. 12, pp. 1792-1796, Dec. 2016. [PDF] [Code@github]