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HSIToolbox: A web-based application for the classification of hyperspectral images
oleh: Zeno Dhaene, Nina Žižakić, Shaoguang Huang, Xian Li, Aleksandra Pižurica
Format: | Article |
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Diterbitkan: | Elsevier 2023-05-01 |
Deskripsi
Recent deep-learning-based classification models for hyperspectral images (HSIs) yield near-perfect classification accuracy on benchmark data sets. However, applying them in real scenarios often requires programming skills and machine learning expertise, which makes the usage of these algorithms unfriendly for domain experts. In this paper, we provide a web-based application, HSIToolbox, for the classification of HSI with a user-friendly graphical interface, which allows a domain expert to view, label and manage HSIs, and to train out-of-the-box deep learning models on the server. HSIToolbox supports different operating systems and different HSI data formats. With a developed queuing system and web interface, HSIToolbox can be accessed remotely by multiple users at the same time.