Automatic target recognition on synthetic aperture radar imagery: A survey
Automatic target recognition (ATR) for military applications is one of the core processes
toward enhancing intelligence and autonomously operating military platforms. Spurred by …
toward enhancing intelligence and autonomously operating military platforms. Spurred by …
A survey on the applications of convolutional neural networks for synthetic aperture radar: Recent advances
In recent years, convolutional neural networks (CNNs) have drawn considerable attention
for the analysis of synthetic aperture radar (SAR) data. In this study, major subareas of SAR …
for the analysis of synthetic aperture radar (SAR) data. In this study, major subareas of SAR …
Hybrid inference network for few-shot SAR automatic target recognition
Synthetic aperture radar (SAR) automatic target recognition (ATR) plays an important role in
SAR image interpretation. However, at least hundreds of training samples are usually …
SAR image interpretation. However, at least hundreds of training samples are usually …
SAR target classification using the multikernel-size feature fusion-based convolutional neural network
It is well-known that the convolutional neural network (CNN) is an effective method for
synthetic aperture radar (SAR) target classification. In the convolutional layer of CNN …
synthetic aperture radar (SAR) target classification. In the convolutional layer of CNN …
[HTML][HTML] A deep learning multi-layer perceptron and remote sensing approach for soil health based crop yield estimation
Abstract In recent years, Deep Learning Multi-Layer Perceptron (DLMLP) neural networks
have shown remarkable success in addressing crop yield forecast related problems. The …
have shown remarkable success in addressing crop yield forecast related problems. The …
Adversarial examples for CNN-based SAR image classification: An experience study
Synthetic aperture radar (SAR) has all-day and all-weather characteristics and plays an
extremely important role in the military field. The breakthroughs in deep learning methods …
extremely important role in the military field. The breakthroughs in deep learning methods …
Multi-scale deep feature learning network with bilateral filtering for SAR image classification
J Geng, W Jiang, X Deng - ISPRS Journal of Photogrammetry and Remote …, 2020 - Elsevier
Synthetic aperture radar (SAR) image classification using deep neural network has drawn
great attention, which generally requires various layers of deep model for feature learning …
great attention, which generally requires various layers of deep model for feature learning …
YOLO-SD: Small ship detection in SAR images by multi-scale convolution and feature transformer module
S Wang, S Gao, L Zhou, R Liu, H Zhang, J Liu, Y Jia… - Remote Sensing, 2022 - mdpi.com
As an outstanding method for ocean monitoring, synthetic aperture radar (SAR) has
received much attention from scholars in recent years. With the rapid advances in the field of …
received much attention from scholars in recent years. With the rapid advances in the field of …
A comprehensive survey of machine learning applied to radar signal processing
P Lang, X Fu, M Martorella, J Dong, R Qin… - arxiv preprint arxiv …, 2020 - arxiv.org
Modern radar systems have high requirements in terms of accuracy, robustness and real-
time capability when operating on increasingly complex electromagnetic environments …
time capability when operating on increasingly complex electromagnetic environments …
SoftFormer: SAR-optical fusion transformer for urban land use and land cover classification
Classification of urban land use and land cover is vital to many applications, and naturally
becomes a popular topic in remote sensing. The finite information carried by unimodal data …
becomes a popular topic in remote sensing. The finite information carried by unimodal data …