Continual Learning of Micro-Doppler Signature-Based Human Activity Classification

• Published in: IEEE geoscience and remote sensing letters Vol. 19; pp. 1 - 5
• Main Authors: Lee, Donggyu, Park, Hyeongmin, Moon, Taesup, Kim, Youngwook
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Artificial neural networks; Classification; Comparative analysis; Comparative studies; Competitiveness; Continual learning; deep convolutional neural networks (DCNNs); Doppler sonar; human activity classification; Learning algorithms; Learning systems; Machine learning; Methods; micro-Doppler; Neural networks; Radar; Radar data; Radar imaging; Radar signatures; Rescue operations; Search and rescue missions; Spectrogram; Task analysis; Training; Training data

Human activity classification based on micro-Doppler signatures measured by radar recently has been successfully applied in diverse applications due to the improvement of machine learning methods, e.g., deep convolutional neural networks (DCNNs). Despite the success, those methods encounter a common...