تقرير
Hyperspectral Reconstruction of Skin Through Fusion of Scattering Transform Features
| العنوان: | Hyperspectral Reconstruction of Skin Through Fusion of Scattering Transform Features |
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| المؤلفون: | Czaja, Wojciech, Emidih, Jeremiah, Kolstoe, Brandon, Spencer, Richard G. |
| سنة النشر: | 2024 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Machine Learning |
| الوصف: | Hyperspectral imagery (HSI) is an established technique with an array of applications, but its use is limited due to both practical and technical issues associated with spectral devices. The goal of the ICASSP 2024 'Hyper-Skin' Challenge is to extract skin HSI from matching RGB images and an infrared band. To address this problem we propose a model using features of the scattering transform - a type of convolutional neural network with predefined filters. Our model matches and inverts those features, rather than the pixel values, reducing the complexity of matching while grouping similar features together, resulting in an improved learning process. Comment: Corresponding Author: bkolstoe@umd.edu Presented at ICASSP 2024 |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2404.10030 |
| رقم الأكسشن: | edsarx.2404.10030 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |