isprs journal of photogrammetry and remote sensing deep learning in remote sensing applications: a meta-analysis and review L Ma,Y Liu,X Zhang,... 被引量: 0发表: 0年 Deep learning in remote sensing: a review Standing at the paradigm shift towards data-intensive science, machine learning ...
5、Deep learning in remote sensing applications: A meta-analysis and review 6、Deep learning classifiers for hyperspectral imaging: A review 7、Deep Learning for Classification of Hyperspectral Data: A Comparative Review 8、Deep neural network for remote sensing image interpretation: status and perspecti...
Deep learning in remote sensing applications: A meta-analysis and review ISPRS J. Photogramm. Remote Sens., 152 (2019), pp. 166-177, 10.1016/j.isprsjprs.2019.04.015 Google Scholar Ma and Liu, 2020 W. Ma, Y. Liu A data-efficient self-supervised deep learning model for design and charac...
A. Johnson, “Deep learning in remote sensing applications: A meta-analysis and review,” ISPRS Journal of Photogrammetry and Remote Sensing, vol. 152, pp. 166–177, 6 2019. [18] T. Hoeser and C. Kuenzer, “Object Detection and Image Segmentation with Deep Learning on Earth Observation...
Deep-learning (DL) algorithms, which learn the representative and discriminative features in a hierarchical manner from the data, have recently become a hotspot in the machine-learning area and have been introduced into the geoscience and remote sensing (RS) community for RS big data analysis. Con...
Deep learning in remote sensing applications: A meta-analysis and review. ISPRS J. Photogramm. Remote Sens. 2019, 152, 166–177. [Google Scholar] [CrossRef] Yekeen, S.T.; Balogun, A.; Yusof, K.B.W. A novel deep learning instance segmentation model for automated marine oil spill ...
Figure 1. Deep learning in multiscale agricultural sensing. Motivated by the rapid development of precision agriculture and deep learning, in this work, we have conducted a comprehensive review on the applications of DL for multiscale agricultural remote/proximal sensing. The term “deep learning”...
Context-self contrastive pretraining for crop type semantic segmentation- Published in IEEE Transactions on Geoscience and Remote Sensing, this work introduces a novel supervised pretraining method for semantic segmentation of crop types exhibiti performance gains along object boundaries. Additional informatio...
Deep transfer learning and its applications in remote sensing and computer vision An important success and use of Deep Learning in recent years has been in the field of image processing. Research on Deep Learning has shown that these arc... J Lin 被引量: 0发表: 2020年 Breaking Limits of ...
Deep learning in environmental remote sensing: Achievements and challenges 2020, Remote Sensing of Environment Show abstract Deep learning in remote sensing applications: A meta-analysis and review 2019, ISPRS Journal of Photogrammetry and Remote Sensing Show abstract Deep learning and process understanding...