Complex-valued neural networks: A comprehensive survey
Complex-valued neural networks (CVNNs) have shown their excellent efficiency compared
to their real counter-parts in speech enhancement, image and signal processing …
to their real counter-parts in speech enhancement, image and signal processing …
Three decades of activations: A comprehensive survey of 400 activation functions for neural networks
Neural networks have proven to be a highly effective tool for solving complex problems in
many areas of life. Recently, their importance and practical usability have further been …
many areas of life. Recently, their importance and practical usability have further been …
Sparse synthetic aperture radar imaging from compressed sensing and machine learning: Theories, applications, and trends
Synthetic aperture radar (SAR) image formation can be treated as a class of ill-posed linear
inverse problems, and the resolution is limited by the data bandwidth for traditional imaging …
inverse problems, and the resolution is limited by the data bandwidth for traditional imaging …
Deep learning meets SAR: Concepts, models, pitfalls, and perspectives
Deep learning in remote sensing has received considerable international hype, but it is
mostly limited to the evaluation of optical data. Although deep learning has been introduced …
mostly limited to the evaluation of optical data. Although deep learning has been introduced …
A survey on the new generation of deep learning in image processing
During the past decade, deep learning is one of the essential breakthroughs made in
artificial intelligence. In particular, it has achieved great success in image processing …
artificial intelligence. In particular, it has achieved great success in image processing …
A survey of complex-valued neural networks
Artificial neural networks (ANNs) based machine learning models and especially deep
learning models have been widely applied in computer vision, signal processing, wireless …
learning models have been widely applied in computer vision, signal processing, wireless …
Fully complex-valued dendritic neuron model
A single dendritic neuron model (DNM) that owns the nonlinear information processing
ability of dendrites has been widely used for classification and prediction. Complex-valued …
ability of dendrites has been widely used for classification and prediction. Complex-valued …
AF-AMPNet: A deep learning approach for sparse aperture ISAR imaging and autofocusing
Inverse synthetic aperture radar (ISAR) imaging and autofocusing are challenging under
sparse aperture (SA) conditions. Traditional imaging or autofocusing methods fail to obtain …
sparse aperture (SA) conditions. Traditional imaging or autofocusing methods fail to obtain …
RMIST-Net: Joint range migration and sparse reconstruction network for 3-D mmW imaging
Compressed sensing (CS) demonstrates significant potential to improve image quality in 3-
D millimeter-wave imaging compared with conventional matched filtering (MF). However …
D millimeter-wave imaging compared with conventional matched filtering (MF). However …
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 …