Classification of hyperspectral images based on fused 3D inception and 3D-2D hybrid convolution-Reference-Cited by-同舟云学术

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Classification of hyperspectral images based on fused 3D inception and 3D-2D hybrid convolution

Published:2024-01-20 Issue:4 Volume:18 Page:3031-3041
ISSN:1863-1703
Container-title:Signal, Image and Video Processing
language:en
Short-container-title:SIViP

Author:

Shen Jingke,Zhang Denghong,Dong Guanghui,Sun Duixiong,Liang Xiyin,Su Maogen

Funder

the Traditional Chinese Medicine Industry Innovation Consortium Project of Gansu Province

the Industrial Support Project of Gansu Province

the Science and Technology Project of Gansu Province

Lanzhou Talent Innovation and Entrepreneurship Project

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s11760-023-02968-3.pdf

Reference27 articles.

1. Strack, R.: Capturing hyperspectral images. Nat. Methods 20(6), 783 (2023)

2. Picot-Clemente, J.: Hyperspectral imaging’s potential for transforming the imaging field. Laser Focus World 59(4), 20–24 (2023)

3. Taghinezhad, E., Szumny, A., Figiel, A.: The application of hyperspectral imaging technologies for the prediction and measurement of the moisture content of various agricultural crops during the drying process. Molecules 28(7), 2930 (2023)

4. Elbasuney, S., Mahmoud, A., El-Sharkawy, Y.H.: Novel molecular laser-induced photoluminscence signature with hyperspectral imaging for instant and remote detection of trace explosive materials. Talanta 266, 124978 (2024)

5. Stuart, M.B., Davies, M., Hobbs, M.J., Pering, T.D., McGonigle, A.J., Willmott, J.R.: High-resolution hyperspectral imaging using low-cost components: application within environmental monitoring scenarios. Sensors 22(12), 4652 (2022)

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