Multitemporal Very High Resolution From Space: Outcome of the 2016 IEEE GRSS Data Fusion Contest

Multitemporal Very High Resolution From Space: Outcome of the 2016 IEEE GRSS Data Fusion Contest

In this paper, the scientific outcomes of the 2016 Data Fusion Contest organized by the Image Analysis and Data Fusion Technical Committee of the IEEE Geoscience and Remote Sensing Society are discussed. The 2016 Contest was an open topic competition based on a multitemporal and multimodal dataset,...

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Bibliographic Details
Main Authors: L. Mou, X. Zhu, M. Vakalopoulou, K. Karantzalos, N. Paragios, B. Le Saux, G. Moser, D. Tuia
Format: Article
Language:English
Published: IEEE 2017-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Change detection
convolutional neural networks (CNN)
deep learning
image analysis and data fusion
multiresolution
multisource
Online Access:https://ieeexplore.ieee.org/document/7948767/

Internet

https://ieeexplore.ieee.org/document/7948767/

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