Search Results for author:
Found 7 papers, 4 papers with code
LDSF: Lightweight Dual-Stream Framework for SAR Target Recognition by Coupling Local Electromagnetic Scattering Features and Global Visual Features
We extract the EM scattering (EMS) information from the complex SAR data and integrate the physical properties of the target into the network through a dual-stream framework to guide the network to learn physically meaningful and discriminative features.
Towards Assessing the Synthetic-to-Measured Adversarial Vulnerability of SAR ATR
Recently, there has been increasing concern about the vulnerability of deep neural network (DNN)-based synthetic aperture radar (SAR) automatic target recognition (ATR) to adversarial attacks, where a DNN could be easily deceived by clean input with imperceptible but aggressive perturbations.
Predicting Gradient is Better: Exploring Self-Supervised Learning for SAR ATR with a Joint-Embedding Predictive Architecture
Besides, we employ local masks and multi-scale features to accommodate the various small targets in remote sensing.
Deep Intellectual Property Protection: A Survey
Deep Neural Networks (DNNs), from AlexNet to ResNet to ChatGPT, have made revolutionary progress in recent years, and are widely used in various fields.
Boosting Convolutional Neural Networks with Middle Spectrum Grouped Convolution
This paper proposes a novel module called middle spectrum grouped convolution (MSGC) for efficient deep convolutional neural networks (DCNNs) with the mechanism of grouped convolution.
Hierarchical Disentanglement-Alignment Network for Robust SAR Vehicle Recognition
However, robustly recognizing vehicle targets is a challenging task in SAR due to the large intraclass variations and small interclass variations.
Single-stage Rotate Object Detector via Two Points with Solar Corona Heatmap
In this study, we developed a single-stage rotating object detector via two points with a solar corona heatmap (ROTP) to detect oriented objects.
