Nov 28, 2023 · Abstract: Hyperspectral anomaly detection (HAD) aims to identify anomalous targets that deviate from the surrounding background in unlabeled ...
Hyperspectral anomaly detection (HAD) aims to identify anomalous targets that deviate from the surrounding background in unlabeled hyperspectral images ...
Nov 20, 2023 · Hyperspectral anomaly detection (HAD) aims to identify anomalous objects that deviate from surrounding backgrounds in an unlabeled hyperspectral ...
Blind-block reconstruction network with a guard window for ...
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Abstract. Most existing depth networks that perform hyperspectral anomaly detection (HAD) using reconstruction errors tend to fit anomalous pixels, ...
BockNet creates a blind-block (guard window) in the center of the network's receptive field, rendering it unable to see the information inside the guard window ...
Abstract ; Publication: IEEE Transactions on Geoscience and Remote Sensing ; Pub Date: 2023 ; DOI: 10.1109/TGRS.2023.3335484 ; Bibcode: 2023ITGRS..6135484W.
The reconstructed HSI can be regarded as a pure background HSI, and the reconstruction error of anomalous pixels will be further enlarged, thus improving ...
BockNet: Blind-Block Reconstruction Network With a Guard Window for Hyperspectral Anomaly Detection ... Authors: Degang Wang; Lina Zhuang; Lianru Gao; Xu Sun; Min ...
People also ask
What is hyperspectral anomaly detection?
Hyperspec- tral anomaly detection aims to find targets without pri- or knowledge, which has attracted attention as a branch of target location.
In order to achieve a superior background reconstruction network for HAD purposes, this paper proposes a self-supervised blind-block network (termed BockNet) ...
I'm currently a Ph.D. student at the Chinese Academy of Sciences, and I am now focusing on hyperspectral target detection and deep learning. - DegangWang97.