光谱图
自编码
计算机科学
人工智能
对抗制
特征(语言学)
生成语法
深度学习
模式识别(心理学)
无监督学习
特征学习
领域(数学分析)
人工神经网络
机器学习
语音识别
数学
数学分析
哲学
语言学
作者
Hannah Garcia Doherty,Lorenzo Cifola,R. I. A. Harmanny,Francesco Fioranelli
出处
期刊:European Radar Conference
日期:2019-11-21
被引量:8
摘要
This paper presents the implementation of a Generative Adversarial Network (GAN) and Adversarial Autoencoder (AAE) trained in an unsupervised manner using micro-Doppler (mD) spectrograms of human gait. Once the GAN network was trained, the domain where micro-Doppler feature learning happens is inspected. This domain is then accessed by building the AAE and different network visualizations are shown. The benefits of unsupervised training are highlighted by investigating the self-learned spectrogram features, revealing the potential of unsupervised adversarial training techniques for mD spectrogram feature learning methods.
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