1 citations · 1 across the 2 of their papers we have counts for
3 papers
General Feature Extraction In SAR Target Classification: A Contrastive Learning Approach Across Sensor Types
M. Muzeau, J. Frontera-Pons, Chengfang Ren +1
The increased availability of SAR data has raised a growing interest in applying deep learning algorithms. However, the limited availability of labeled data poses a significant cha…
SAFE: a SAR Feature Extractor based on self-supervised learning and masked Siamese ViTs
Max Muzeau, Joana Frontera-Pons, Chengfang Ren +1
Due to its all-weather and day-and-night capabilities, Synthetic Aperture Radar imagery is essential for various applications such as disaster management, earth monitoring, change…
Deep Learning-Based Anomaly Detection in Synthetic Aperture Radar Imaging
Max Muzeau, Chengfang Ren, Sébastien Angelliaume +2
In this paper, we proposed to investigate unsupervised anomaly detection in Synthetic Aperture Radar (SAR) images. Our approach considers anomalies as abnormal patterns that deviat…