In this paper, we apply the NN approach to the classification of multi-temporal LANDSAT TM images in order to investigate the robustness of the two ...
Neural net classifier for multi-temporal LANDSAT TM images ...
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We have proposed an NN model to combine the spectral and spacial information of a LANDSAT TM image. In this paper, we apply the NN approach with a normalization ...
This paper illustrates problems and solutions for the design and configuration of neural network architectures used to classify remotely sensed multi-temporal ...
The main objective of this study is to compare sigmoid, tangent hyper- bolic, and linear activation functions through the one- and two-hidden layered MLP neural ...
In recent years, multitemporal images have been widely used to construct time series images (TSIs) and have achieved great success in land cover classification ...
A series of experiments are conducted on a feed-forward backpropagation neural network which is used to classify land cover from Landsat TM data.
Results show that the neural network approach is an attractive and effective way of extracting land cover information using multi-spectral, multi-temporal and ...
Jan 21, 2024 · In this letter we evaluate the ability of Recurrent Neural Networks, in particular the Long-Short Term Memory (LSTM) model, to perform land ...
The authors apply the NN approach with a normalization method to classify multi-temporal LANDSAT TM images in order to investigate the robustness of their�...
Jun 10, 2024 · This study describes a novel three-dimensional (3D) convolutional neural networks (CNN) based method that automatically classifies crops ...