Identifying and counting of buildings using artificial neural network and reduced representation in high-resolution images-Reference-Cited by-同舟云学术

Identifying and counting of buildings using artificial neural network and reduced representation in high-resolution images

Published:2021-05-17 Issue: Volume: Page:1-16
ISSN:1010-6049
Container-title:Geocarto International
language:en
Short-container-title:Geocarto International

Author:

Chakraborty Debasish¹,Chowdhury Sandipan²

Affiliation:

1. Regional Remote Sensing Centre-East, National Remote Sensing Centre, ISRO, New Town, Kolkata, West Bengal, India

2. Department of Information Technology, Government College of Engineering and Ceramic Technology, Kolkata, West Bengal, India

Publisher

Informa UK Limited

Subject

Water Science and Technology,Geography, Planning and Development

Link

https://www.tandfonline.com/doi/pdf/10.1080/10106049.2021.1923825

Reference32 articles.

1. Using Convolutional Networks and Satellite Imagery to Identify Patterns in Urban Environments at a Large Scale

2. Support Vector Machines for Object Based Building Extraction in Suburban Area using Very High Resolution Satellite Images, a Case Study: Tetuan, Morocco

3. Bourissou A, Pham K, Levy-Vehel J. 1994. A multifractal approach for terrain characterization and classification on SAR images; IGARSS 3. 1609–1611.

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