A Novel Multilevel Pulse Coupled Neural Networks Architecture for Objects Recognition Applied on ASI Cosmo-Skymed Data
Author:
Affiliation:
1. Italian Space Agency (ASI),Rome,Italy
2. Tor Vergata University,Department of Civil Engineering and Computer Science Engineering (DICII),Rome,Italy
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10640349/10640352/10640619.pdf?arnumber=10640619
Reference7 articles.
1. Toward Fully Automatic Detection of Changes in Suburban Areas From VHR SAR Images by Combining Multiple Neural-Network Models
2. COSMO-SkyMed for Unsupervised Urban Change Detection using Radar Backscattering and Interferometric Coherence
3. Sentinel-1 and Sentinel-2 Data Fusion for Urban Change Detection
4. Recent Advances in Pulse-Coupled Neural Networks with Applications in Image Processing
5. A Review of the Exploitation of the Operational Mission COSMO-SkyMed: Global Trends (2014-2017)
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