Htun, Phyu Phyu and Boschetti, Marco and Buriro, Attaullah and Confalonieri, Roberto and Sun, Boyuan and Htwe, Ah Nge and Tillo, Tammam (2021) A Lightweight Approach For Wood Hyperspectral Images Classification. In: 2021 IEEE International Conference on Multimedia & Expo Workshops (ICMEW), 2021-07-05 - 2021-07-09, Shenzhen, China.
Htun, Phyu Phyu and Boschetti, Marco and Buriro, Attaullah and Confalonieri, Roberto and Sun, Boyuan and Htwe, Ah Nge and Tillo, Tammam (2021) A Lightweight Approach For Wood Hyperspectral Images Classification. In: 2021 IEEE International Conference on Multimedia & Expo Workshops (ICMEW), 2021-07-05 - 2021-07-09, Shenzhen, China.
Htun, Phyu Phyu and Boschetti, Marco and Buriro, Attaullah and Confalonieri, Roberto and Sun, Boyuan and Htwe, Ah Nge and Tillo, Tammam (2021) A Lightweight Approach For Wood Hyperspectral Images Classification. In: 2021 IEEE International Conference on Multimedia & Expo Workshops (ICMEW), 2021-07-05 - 2021-07-09, Shenzhen, China.
Abstract
This paper presents a Convolutional Neural Network (CNN)based spatial classifier to classify hyperspectral images for wood recognition. The spatial classifier is built by adapting the input and output units of Cifar10Net, a conventional image classifier that accepts three-band images as input. Obtained results in terms of accuracy and training time show that the proposed classifier can be trained using few training data, and few computational resources.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Uncontrolled Keywords: | Hyperspectral images classification; computer vision; wood recognition |
| Divisions: | Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
| SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
| Depositing User: | Unnamed user with email elements@essex.ac.uk |
| Date Deposited: | 20 Aug 2025 16:29 |
| Last Modified: | 20 Aug 2025 16:30 |
| URI: | http://repository.essex.ac.uk/id/eprint/40856 |