Nov 25, 2023 · In this paper, SAR images are classified using the proposed convolutional neural network. The limitation of data concerning moving and stationary target ...

First, we utilize the weights learned by the training network, and second, we keep negative neurons and neurons close to zero active instead of deactivating ...

First, we utilize the weights learned by the training network, and second, we keep negative neurons and neurons close to zero active instead of deactivating ...

In this paper, the Convolution neural network based(CNN) image classification is evaluated by changing the parameters of CNN like number of layers, number of ...

First, we utilize the weights learned by the training network, and second, we keep negative neurons and neurons close to zero active instead of deactivating ...

Convolutional Neural Network (CNN) has attracted much at- tention for feature learning and image classification, mostly related to close range photography.

The major purpose of this work is to make a development on introducing a new framework for SAR image segmentation and categorization using deep learning.

This thesis shows that cross-modality transfer learning from features learned on photographs to SAR images is effective and that shallow classification ...

Dec 9, 2022 · SAR image target detection based on the Convolutional Neural Network (CNN) is reviewed in this paper. Firstly, the traditional SAR image target detection ...

In this paper, we first propose a novel physically explainable convolutional neural network for SAR image classification, namely physics guided and injected ...