Lichao Mou

PhD candidate

IMF-DLR & SiPEO-TUM

lichao.mou[at]dlr.de

Google scholar / Research gate

Research

I'm interested in algorithms for remote sensing data analysis and visual tasks. My work explores topics in remote sensing, computer vision, and machine/deep learning.

Have a look at what I am doing -> Demos

Selected publications

2019

  • Lichao Mou, Lorenzo Bruzzone, and Xiao Xiang Zhu. Learning spectral-spatial-temporal features via a recurrent convolutional neural network for change detection in multispectral imagery. IEEE Transactions on Geoscience and Remote Sensing, vol. 57, no. 2, pp. 924-935, 2019. [link] [Featured on Journal Cover]
  • Yuansheng Hua*, Lichao Mou*, and Xiao Xiang Zhu. Recurrently exploring class-wise attention in a hybrid convolutional and bidirectional LSTM network for multi-label aerial image classification. ISPRS Journal of Photogrammetry and Remote Sensing, vol. 149, pp. 188-199, 2019. [link] (* equal contribution)
  • Qingpeng Li, Lichao Mou, Qizhi Xu, Yun Zhang, and Xiao Xiang Zhu. R3-Net: A deep network for multioriented vehicle detection in aerial images and videos. IEEE Transactions on Geoscience and Remote Sensing, DOI:10.1109/TGRS.2019.2895362.

2018

  • Lichao Mou, Pedram Ghamisi, and Xiao Xiang Zhu. Unsupervised spectral-spatial feature learning via deep residual conv-deconv network for hyperspectral image classification. IEEE Transactions on Geoscience and Remote Sensing, vol. 56, no. 1, pp. 391-406, 2018. [link] [ESI Highly Cited Paper]
  • Lichao Mou and Xiao Xiang Zhu. Vehicle instance segmentation from aerial image and video using a multi-task learning residual fully convolutional network. IEEE Transactions on Geoscience and Remote Sensing, vol. 56, no. 11, pp. 6699-6711, 2018. [link]
  • Qingpeng Li, Lichao Mou, Qingjie Liu, Yunhong Wang, and Xiao Xiang Zhu. HSF-Net: Multi-scale deep feature embedding for ship detection in optical remote sensing imagery. IEEE Transactions on Geoscience and Remote Sensing, vol. 56, no. 12, pp. 7147-7161, 2018. [link]

2017

  • Xiao Xiang Zhu, Devis Tuia, Lichao Mou, Gui-Song Xia, Liangpei Zhang, Feng Xu, and Friedrich Fraundorfer. Deep learning in remote sensing: A comprehensive review and list of resources. IEEE Geoscience and Remote Sensing Magazine, vol. 5, no. 4, pp. 8-36, 2017. [link] [ESI Hot Paper]
  • Lichao Mou, Pedram Ghamisi, and Xiao Xiang Zhu. Deep recurrent neural networks for hyperspectral image classification. IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no. 7, pp. 3639-3655, 2017. [link] [ESI Hot Paper]

2016

  • Lichao Mou and Xiao Xiang Zhu. Spatiotemporal scene interpretation of space videos via deep neural network and tracklet analysis. In IGARSS, 2016.
  • Haobo Lyu*, Hui Lu, and Lichao Mou*. Learning a transferable change rule from a recurrent neural network for land cover change detection . Remote Sensing, vol. 8, no. 6, p. 506, 2016. [link] (* equal contribution)

2015

  • Yuan Yuan, Lichao Mou, and Xiaoqiang Lu. Scene recognition by manifold regularized deep learning architecture. IEEE Transactions on Neural Networks and Learning Systems, vol. 26, no. 10, pp. 2222-2233, 2015. [link]
  • Xuelong Li, Lichao Mou, and Xiaoqiang Lu. Scene parsing from an MAP perspective. IEEE Transactions on Cybernetics, vol. 45, no. 9, pp. 1876-1886, 2015. [link]
  • Xiaoqiang Lu, Xuelong Li, and Lichao Mou. Semi-supervised multitask learning for scene recognition. IEEE Transactions on Cybernetics, vol. 45, no. 9, pp. 1967-1976, 2015. [link] [ESI Highly Cited Paper]