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

Publication

[Preprints]

  • Q. Li, L. Mou, Q. Xu, Y. Zhang, and X. X. Zhu, "R3-Net: A deep network for multi-oriented vehicle detection in aerial images and videos," arXiv:1808.05560. [arXiv link] [video demo]
  • Y. Hua, L. Mou, and X. X. Zhu, "Recurrently exploring class-wise attention in a hybrid convolutional and bidirectional LSTM network for multi-label aerial image classification," arXiv:1807.11245. [arXiv link]
  • L. Mou and X. X. Zhu, "RiFCN: Recurrent network in fully convolutional network for semantic segmentation of high resolution remote sensing images," arXiv:1805.02091, 2018. [arXiv link]
  • L. Mou and X. X. Zhu, "IM2HEIGHT: Height estimation from single monocular imagery via fully residual convolutional-deconvolutional network," arXiv:1802.10249, 2018. [arXiv link]

[Journal Articles]

  • C. Qiu, M. Schmitt, L. Mou, P. Ghamisi, and X. X. Zhu, "Feature importance analysis for Local Climate Zone classification using a residual convolutional neural network with multi-source datasets," Remote Sensing, vol. 10, no. 10, p. 1572, 2018. [link]
  • L. Mou, L. Bruzzone, and X. X. 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, in press. [arXiv link]
  • Q. Li, L. Mou, Q. Liu, Y. Wang, and X. X. Zhu, "HSF-Net: Multi-scale deep feature embedding for ship detection in optical remote sensing imagery," IEEE Transactions on Geoscience and Remote Sensing, DOI: 10.1109/TGRS.2018.2848901. [link]
  • L. Mou and X. X. 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, DOI: 10.1109/TGRS.2018.2841808. [link] [dataset]
  • H. Lyu*, H. Lu, L. Mou*, W. Li, J. Wright, X. Li, X. Li, X. X. Zhu, J. Wang, L. Yu, and P. Gong, "Long-term annual mapping of four cities on different continents by applying a deep information learning method to Landsat data," Remote Sensing, vol. 10, no. 3, p. 471, 2018. [link] (* equal contribution)
  • L. Hughes, M. Schmitt, L. Mou, Y. Wang, and X. X. Zhu, "Identifying corresponding patches in SAR and optical images with a pseudo-Siamese CNN," IEEE Geoscience and Remote Sensing Letters, vol. 15, no. 5, pp. 784-788, 2018. [link]
  • L. Mou, P. Ghamisi, and X. X. 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]
  • X. X. Zhu, D. Tuia, L. Mou, G.-S. Xia, L. Zhang, F. Xu, and F. 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 Highly Cited Paper] [Monthly most popular article of IEEE Geosci. Remote Sens. Mag. from Jan. 2018 to Aug. 2018]
  • L. Mou, P. Ghamisi, and X. X. 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 Highly Cited Paper] [Monthly most popular article of IEEE Trans. Geosci. Remote Sens. from Jul. 2017 to Aug. 2018]
  • L. Mou, X. X. Zhu, M. Vakalopoulou, K. Karantzalos, N. Paragios, B. Le Saux, G. Moser, and D. Tuia, "Multitemporal very high resolution from space: Outcome of the 2016 IEEE GRSS Data Fusion Contest," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 10, no. 8, pp. 3435-3447, 2017. [link] [Featured on journal cover] [top-5 monthly most popular articles in Aug. and Sep. 2017]
  • H. Lyu*, H. Lu, and L. 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)
  • X. Li, L. Mou, and X. Lu, "Video parsing via spatiotemporally analysis with images," Multimedia Tools and Applications, vol. 75, no. 19, pp. 11961-11976, 2016. [link]
  • Y. Yuan, L. Mou, and X. 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]
  • X. Li, L. Mou, and X. Lu, "Scene parsing from an MAP perspective," IEEE Transactions on Cybernetics, vol. 45, no. 9, pp. 1876-1886, 2015. [link]
  • X. Lu, X. Li, and L. 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]

[Conference Papers]

  • C. Qiu, M. Schmitt, L. Mou, and X. X. Zhu, "Urban Local Climate Zone classification with a residual convolutional neural network and multi-seasonal Sentinel-2 images," International Workshop on Pattern Recognition in Remote Sensing (PRRS), 2018, Beijing, China.
  • L. Mou and X. X. Zhu, "A recurrent convolutional neural network for land cover change detection in multispectral images," IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2018, Valencia, Spain.
  • Q. Li, L. Mou, K. Jiang, Q. Liu, Y. Wang, and X. X. Zhu, "Hierarchical region based convolution neural network for multiscale object detection in remote sensing images," IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2018, Valencia, Spain.
  • Y. Hua, L. Mou, and X. X. Zhu, "LAHNet: A convolutional neural network fusing low- and high-level features for aerial scene classification," IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2018, Valencia, Spain.
  • R. Huang, H. Taubenböck, L. Mou, and X. X. Zhu, "Classification of settlement types from tweets using LDA and LSTM," IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2018, Valencia, Spain.
  • C. Qiu, M. Schmitt, P. Ghamisi, L. Mou, and X. X. Zhu, "Feature importance analysis of Sentinel-2 imagery for large-scale Urban Local Climate Zone classification," IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2018, Valencia, Spain.
  • L. Mou, P. Ghamisi, and X. X. Zhu, "Fully conv-deconv network for unsupervised spectral-spatial feature extraction of hyperspectral imagery via residual learning," IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2017, Fort Worth, Texas, USA. [link]
  • L. Mou, M. Schmitt, Y. Wang, and X. X. Zhu, "Identifying corresponding patches in SAR and optical imagery with a convolutional neural network," IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2017, Fort Worth, Texas, USA. [link]
  • J. Hu, L. Mou, A. Schmitt, and X. X. Zhu, "FusioNet: A two-stream convolutional neural network for urban scene classification using PolSAR and hyperspectral data," Joint Urban Remote Sensing Event (JURSE), 2017, Dubai, UAE. [link]
  • L. Mou, M. Schmitt, Y. Wang, and X. X. Zhu, "A CNN for the identification of corresponding patches in SAR and optical imagery of urban scenes," Joint Urban Remote Sensing Event (JURSE), 2017, Dubai, UAE. [link] [Best Student Paper Award finalist]
  • Y. Wang, X. X. Zhu, S. Montazeri, J. Kang, L. Mou, and M. Schmitt, "Potential of the 'SARptical' system," International Workshop on Advances in the Science and Applications of SAR Interferometry and Sentinel-1 InSAR (FRINGE), 2017, Helsinki, Finland. [link]
  • L. Mou and X. X. Zhu, "Spatiotemporal scene interpretation of space videos via deep neural network and tracklet analysis," IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2016, Beijing, China. [link] [1st place in 2016 IEEE GRSS Data Fusion Contest]
  • L. Mou, X. Lu, and Y. Yuan, "Object or background: Whose call is it in complicated scene classification?" IEEE China Summit and International Conference on Signal and Information Processing (ChinaSIP), 2013, Beijing, China. [link]
  • L. Mou and X. Pan, "Union coding based immune clone selection unsupervised clustering algorithm," International Conference on Computer Application and System Modeling, 2012, Xiamen, China.