Ditapis dengan
Non-linear spectral unmixing of hyperspectral data using Modified PPNMM
Spectral unmixing is one of the unique advantages of hyperspectral images to map the type of species. Such images contain a high spectral resolution making it a classical problem of signal processing at each pixel, which is supposedly formed by the interaction of variously constituted end-members (also known as mixed pixels). Finding the abundance of any feature (or class or end-member) may req…
- Edisi
- Vol.9, March 2021
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 12 hlm PDF, 2.675 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
Hyperspectral unmixing with spatial context and endmember ensemble learning w…
In recent years, transformer-based deep learning networks have gained popularity in Hyperspectral (HS) unmixing applications due to their superior performance. Most of these networks use an Endmember Extraction Algorithm(EEA) for the initialization of their network. As EEAs performance depends on the environment, single initialization does not ensure optimum performance. Also, only a few networ…
- Edisi
- Vol.15, January 2025
- ISBN/ISSN
- 1872-8235
- Deskripsi Fisik
- 18 hlm PDF, 7.321 KB
- Judul Seri
- ISPRS Open Journal of Photogrammetry and Remote Sensing
- No. Panggil
- 621.3678
Batas Wilayah 
Ekologi 
Fotogrametri 
Geografi 
Geologi 
GIS 
Ilmu Tanah 
Kartografi 
Manajemen Bencana 
Oceanografi 
Penginderaan Jauh 
Peta