Towards Energy-Efficient Hyperspectral Image Processing Inside Camera Pixels-Reference-Cited by-同舟云学术

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Towards Energy-Efficient Hyperspectral Image Processing Inside Camera Pixels

Published:2023 Issue: Volume: Page:303-316
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
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Author:

Datta Gourav,Yin Zihan,Jacob Ajey P.,Jaiswal Akhilesh R.,Beerel Peter A.

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-25075-0_22

Reference40 articles.

1. Alhamzi, K., et al.: 3D object recognition based on image features: a survey. Int. J. Comput. Inf. Technol. (IJCIT) 3, 651–660 (2014)

2. Lv, Z., et al.: Real-time image processing for augmented reality on mobile devices. J. Real-Time Image Process. 18, 245–248 (2021)

3. Facciolo, G., et al.: Automatic 3D reconstruction from multi-date satellite images. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). vol. 1, 1542–1551 (2017)

4. Chen, Y., et al.: Deep learning-based classification of hyperspectral data. IEEE J. Sel. Top. Appl. Earth Observations Remote Sens. 7(6), 2094–2107 (2014)

5. Zheng, Z., et al.: FPGA: fast patch-free global learning framework for fully end-to-end hyperspectral image classification. IEEE Trans. Geosci. Remote Sens. 58(8), 5612–5626 (2020)

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