[HTML][HTML] Incremental Deep Learning for Remote Sensing Image Interpretation
W **ngxing, P Chao, XU Bowen, XIA Guisong - 电子与信息学报, 2024 - jeit.ac.cn
The significant advancement of deep learning has facilitated the emergence of high-
precision interpretation models for remote-sensing images. However, a notable drawback is …
precision interpretation models for remote-sensing images. However, a notable drawback is …
[HTML][HTML] 面向遥感图像解译的增量深度学**
翁星星， 庞超， 许博文， 夏桂松 - 电子与信息学报, 2022 - jeit.ac.cn
深度学**的发展推动了高精度遥感图像智能解译模型的涌现. 然而, 目前遥感智能解译模型大多
基于预先定义的静态数据集独立训练, 难以适应环境开放和需求动态的实际应用 …
基于预先定义的静态数据集独立训练, 难以适应环境开放和需求动态的实际应用 …
Few-Shot Class-Incremental SAR Image Target Recognition using Self-supervised Decoupled Dynamic Classifier
Y ZHAO, L ZHAO, S ZHANG, K JI, G KUANG - 电子与信息学报, 2022 - jeit.ac.cn
Abstract To power Deep-Learning (DL) based Synthetic Aperture Radar Automatic Target
Recognition (SAR ATR) systems with the capability of learning new-class targets …
Recognition (SAR ATR) systems with the capability of learning new-class targets …
[PDF][PDF] 自监督解耦动态分类器的小样本类增量 SAR 图像目标识别
赵琰， 赵凌君， 张思乾， 计科峰， 匡纲要 - 电子与信息学报, 2022 - jeit.ac.cn
为提升基于深度学**(DL) 的合成孔径雷达自动目标识别(SAR ATR) 系统在开放动态的非合作
场景中对新类别目标的持续敏捷识别能力, 该文研究了SAR ATR 的小样本类增量学**(FSCIL) …
场景中对新类别目标的持续敏捷识别能力, 该文研究了SAR ATR 的小样本类增量学**(FSCIL) …