Classification of multisensor remote-sensing images by structured neural networks

SB Serpico, F Roli - … on Geoscience and Remote Sensing, 2002 - ieeexplore.ieee.org
… by any techniques. In particular, we aim to solve such a problem by using neural networks
… To this end, we suggest that each neuron should process a different information aspect and …

Introduction neural networks in remote sensing

PM Atkinson, ARL Tatnall - International Journal of remote sensing, 1997 - Taylor & Francis
… erent types of neural networks (see… features of each type of neural network, this section
provides a brief introduction to the major characteristics of one of the most commonly used neural

A new multi-channel deep convolutional neural network for semantic segmentation of remote sensing image

W Liu, Y Zhang, H Fan, Y Zou, Z Cui - IEEE Access, 2020 - ieeexplore.ieee.org
… the common network can segment RS images to a certain extent, … The common neural
network deepens the network to … to the target spatial features and scale features, and the existing …

Multisource remote sensing data classification based on convolutional neural network

X Xu, W Li, Q Ran, Q Du, L Gao… - … and Remote Sensing, 2017 - ieeexplore.ieee.org
over traditional methods. In this paper, a novel two-branch CNN for multisource remote sensing
data … is designed to combine features extracted from HSI and other source data, such as …

The application of artificial neural networks to the analysis of remotely sensed data

JF Mas, JJ Flores - International Journal of Remote Sensing, 2008 - Taylor & Francis
… image classification based upon neural networks, a number of … reviews remotely sensed
data analysis with neural networks. … features of ANN implementation in some remote sensing

Estimation of physical variables from multichannel remotely sensed imagery using a neural network: Application to rainfall estimation

K Hsu, HV Gupta, X Gao… - Water Resources …, 1999 - Wiley Online Library
several characteristics that make it a less than optimal choice for estimation of physical
variables from remotely sensed data. … to be searched during network training contains numerous …

Artificial neural networks in remote sensing of hydrologic processes

S Islam, R Kothari - Journal of Hydrologic Engineering, 2000 - ascelibrary.org
used multilayer feedforward networks, we also review recurrent neural networks for prediction
and self-organization neuralPoints in the training set can then be used to adjust the …

[КНИГА][B] Methods and algorithms for pre-processing and classification of multichannel radar remote sensing images

GP Kulemin, AA Zelensky, JT Astola, VV Lukin… - 2004 - researchgate.net
… of both characteristics of bare soil regions from multichannel radar remote sensing data. The
… algorithms and software for multichannel radar remote sensing data processing. In general, …

Single-image super resolution for multispectral remote sensing data using convolutional neural networks

L Liebel, M Körner - … , Remote Sensing and Spatial …, 2016 - isprs-archives.copernicus.org
… take into account the special characteristics of multispectral remote sensing data. This dataset
… (2014), is neither possible nor desirable we approach the multichannel dataset as a set of …

Very deep convolutional neural networks for complex land cover mapping using multispectral remote sensing imagery

M Mahdianpari, B Salehi, M Rezaee… - Remote Sensing, 2018 - mdpi.com
… collect spectral information of ground targets at various points of the … for most remote
sensing data. This indicates the significance of developing a pipeline compatible with multi-channel