Improving Pre-Training and Fine-Tuning for Few-Shot SAR Automatic Target Recognition

Pose Estimation for SAR Automatic Target Recognition

This paper explores statistically pose estimation in SAR ATR. Based on our proposed method of maximizing mutual information, further experiments are conducted by using the new MSTAR/ IU Database. Different pose estimator topologies and training criteria are also employed. Experimental results show that our proposed method reduces the average pose estimation error to within 10 degrees of the tru...

Kernel generalized neighbor discriminant embedding for SAR automatic target recognition

In this paper, we propose a new supervised feature extraction algorithm in synthetic aperture radar automatic target recognition (SAR ATR), called generalized neighbor discriminant embedding (GNDE). Based on manifold learning, GNDE integrates class and neighborhood information to enhance discriminative power of extracted feature. Besides, the kernelized counterpart of this algorithm is also pro...

Automatic SAR Target Recognition Using Random Subspace Ensemble Classifiers

Automatic Target Recognition (ATR) has become a widely researched problem due to its applicability in domains such as surveillance systems. It can be implemented on various types of images captured by different sensors. In this paper a novel framework for Automatic Target Recognition (ATR) in Synthetic Aperture Radar (SAR) imagery using Ensemble Classifier is presented. A combination of Princip...

Synthetic Aperture Radar (sar) Automatic Target Recognition (atr) Parametric Study

Roles of Pre-Training and Fine-Tuning in Context-Dependent DBN-HMMs for Real-World Speech Recognition

Recently, deep learning techniques have been successfully applied to automatic speech recognition tasks -first to phonetic recognition with context-independent deep belief network (DBN) hidden Markov models (HMMs) and later to large vocabulary continuous speech recognition using context-dependent (CD) DBN-HMMs. In this paper, we report our most recent experiments designed to understand the role...