Zobrazeno 1 - 10
of 142
pro vyhledávání: '"Mantripragada, Kiran"'
The hyperspectral pixel unmixing aims to find the underlying materials (endmembers) and their proportions (abundances) in pixels of a hyperspectral image. This work extends the Latent Dirichlet Variational Autoencoder (LDVAE) pixel unmixing scheme by
Externí odkaz:
http://arxiv.org/abs/2311.10701
Image segmentation is a fundamental step for the interpretation of Remote Sensing Images. Clustering or segmentation methods usually precede the classification task and are used as support tools for manual labeling. The most common algorithms, such a
Externí odkaz:
http://arxiv.org/abs/2203.02820
We present a method for hyperspectral pixel {\it unmixing}. The proposed method assumes that (1) {\it abundances} can be encoded as Dirichlet distributions and (2) spectra of {\it endmembers} can be represented as multivariate Normal distributions. T
Externí odkaz:
http://arxiv.org/abs/2203.01327
The Effects of Spectral Dimensionality Reduction on Hyperspectral Pixel Classification: A Case Study
This paper presents a systematic study of the effects of hyperspectral pixel dimensionality reduction on the pixel classification task. We use five dimensionality reduction methods -- PCA, KPCA, ICA, AE, and DAE -- to compress 301-dimensional hypersp
Externí odkaz:
http://arxiv.org/abs/2104.00788
Publikováno v:
In ISPRS Journal of Photogrammetry and Remote Sensing January 2021 171:348-366
Several scientific and industry applications require High Performance Computing (HPC) resources to process and/or simulate complex models. Not long ago, companies, research institutes, and universities used to acquire and maintain on-premise computer
Externí odkaz:
http://arxiv.org/abs/1507.05472
High intensive computation applications can usually take days to months to finish an execution. During this time, it is common to have variations of the available resources when considering that such hardware is usually shared among a plurality of re
Externí odkaz:
http://arxiv.org/abs/1412.6392
Autor:
Mantripragada, Kiran K.
Microarray-based comparative genomic hybridization (array-CGH) has emerged as a versatile platform with a wide range of applications in molecular genetics. This thesis focuses on the development of array-CGH with a specific aim to approach disease-re
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-5743
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Mantripragada, Kiran1 (AUTHOR) kiran.mantripragada@ontariotechu.net, Dao, Phuong D.2,3 (AUTHOR), He, Yuhong2 (AUTHOR), Qureshi, Faisal Z.1 (AUTHOR)
Publikováno v:
PLoS ONE. 7/14/2022, Vol. 17 Issue 7, p1-24. 24p.