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You searched for: Journal International journal of remote sensing Remove constraint Journal: International journal of remote sensing Publication Year 2019 Remove constraint Publication Year: 2019 Source 2019 v.40 no.9 Remove constraint Source: 2019 v.40 no.9 Subject algorithms Remove constraint Subject: algorithms Subject hyperspectral imagery Remove constraint Subject: hyperspectral imagery
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1. Densely connected deep random forest for hyperspectral imagery classification

Author:
Cao, Xianghai; Li, Renjie; Ge, Yiming; Wu, Bin; Jiao, Licheng
Source:
International journal of remote sensing 2019 v.40 no.9 pp. 3606-3622
ISSN:
1366-5901
Subject:
algorithms; hyperspectral imagery; models; remote sensing
Abstract:
... In very recent years, deep learning based methods have been widely introduced for the classification of hyperspectral images (HSI). However, these deep models need lots of training samples to tune abundant parameters which induce a heavy computation burden. Therefore, most of these algorithms need to be accelerated with high-performance graphics processing units (GPU). In this paper, a new deep mo ...
DOI:
10.1080/01431161.2018.1547932

2. Unsupervised hyperspectral feature selection based on fuzzy c-means and grey wolf optimizer

Author:
Xie, Fuding; Lei, Cunkuan; Li, Fangfei; Huang, Dan; Yang, Jun
Source:
International journal of remote sensing 2019 v.40 no.9 pp. 3344-3367
ISSN:
1366-5901
Subject:
Aesculus; algorithms; data collection; hyperspectral imagery; remote sensing; selection methods; wolves
Abstract:
... Hyperspectral image (HSI) with hundreds of narrow and consecutive spectral bands provides substantial information to discriminate various land-covers. However, the existence of redundant features/bands not only gives rise to increasing of computation time but also interferes the classification result of hyperspectral images. Obviously, it is a very challenging problem how to select an effective fe ...
DOI:
10.1080/01431161.2018.1541366