246 related articles for article (PubMed ID: 28668006)
1. Hyperspectral sensing data analysis based on quasiconformal mapping-based multiple kernels learning machine.
Li JB; Xie X; Zhai J; Pan JS
Rev Sci Instrum; 2017 Jun; 88(6):065004. PubMed ID: 28668006
[TBL] [Abstract][Full Text] [Related]
2. Linear vs. Nonlinear Extreme Learning Machine for Spectral-Spatial Classification of Hyperspectral Images.
Cao F; Yang Z; Ren J; Jiang M; Ling WK
Sensors (Basel); 2017 Nov; 17(11):. PubMed ID: 29137159
[TBL] [Abstract][Full Text] [Related]
3. Hyperspectral remote sensing image classification based on random average band selection and an ensemble kernel extreme learning machine.
Le BT; Ha TTL
Appl Opt; 2020 May; 59(13):4151-4157. PubMed ID: 32400690
[TBL] [Abstract][Full Text] [Related]
4. A Study on Dimensionality Reduction and Parameters for Hyperspectral Imagery Based on Manifold Learning.
Song W; Zhang X; Yang G; Chen Y; Wang L; Xu H
Sensors (Basel); 2024 Mar; 24(7):. PubMed ID: 38610302
[TBL] [Abstract][Full Text] [Related]
5. Adoption of Machine Learning in Intelligent Terrain Classification of Hyperspectral Remote Sensing Images.
Li Y; Wang J; Gao T; Sun Q; Zhang L; Tang M
Comput Intell Neurosci; 2020; 2020():8886932. PubMed ID: 32952545
[TBL] [Abstract][Full Text] [Related]
6. Potential of DESIS and PRISMA hyperspectral remote sensing data in rock classification and mineral identification:a case study for Banswara in Rajasthan, India.
Tripathi P; Garg RD
Environ Monit Assess; 2023 Apr; 195(5):575. PubMed ID: 37060427
[TBL] [Abstract][Full Text] [Related]
7. Deep Belief Network for Spectral⁻Spatial Classification of Hyperspectral Remote Sensor Data.
Li C; Wang Y; Zhang X; Gao H; Yang Y; Wang J
Sensors (Basel); 2019 Jan; 19(1):. PubMed ID: 30626030
[TBL] [Abstract][Full Text] [Related]
8. Identification of Maize Kernel Vigor under Different Accelerated Aging Times Using Hyperspectral Imaging.
Feng L; Zhu S; Zhang C; Bao Y; Feng X; He Y
Molecules; 2018 Nov; 23(12):. PubMed ID: 30477266
[TBL] [Abstract][Full Text] [Related]
9. Data Field Modeling and Spectral-Spatial Feature Fusion for Hyperspectral Data Classification.
Liu D; Li J
Sensors (Basel); 2016 Dec; 16(12):. PubMed ID: 27999259
[TBL] [Abstract][Full Text] [Related]
10. Image classification of hyperspectral remote sensing using semi-supervised learning algorithm.
Ye A; Zhou X; Weng K; Gong Y; Miao F; Zhao H
Math Biosci Eng; 2023 May; 20(6):11502-11527. PubMed ID: 37322992
[TBL] [Abstract][Full Text] [Related]
11. Hyperspectral Image Classification Based on Improved Rotation Forest Algorithm.
Lv F; Han M
Sensors (Basel); 2018 Oct; 18(11):. PubMed ID: 30360556
[TBL] [Abstract][Full Text] [Related]
12. A Novel Framework for Learning Geometry-Aware Kernels.
Pan B; Chen WS; Xu C; Chen B
IEEE Trans Neural Netw Learn Syst; 2016 May; 27(5):939-51. PubMed ID: 26058057
[TBL] [Abstract][Full Text] [Related]
13. A new hyperspectral image classification method based on spatial-spectral features.
Shenming Q; Xiang L; Zhihua G
Sci Rep; 2022 Jan; 12(1):1541. PubMed ID: 35087142
[TBL] [Abstract][Full Text] [Related]
14. Use of customizing kernel sparse representation for hyperspectral image classification.
Qi B; Zhao C; Yin G
Appl Opt; 2015 Feb; 54(4):707-16. PubMed ID: 25967778
[TBL] [Abstract][Full Text] [Related]
15. Customizing kernel functions for SVM-based hyperspectral image classification.
Guo B; Gunn SR; Damper RI; Nelson JB
IEEE Trans Image Process; 2008 Apr; 17(4):622-9. PubMed ID: 18390369
[TBL] [Abstract][Full Text] [Related]
16. [Hyperspectral remote sensing image classification based on ICA and SVM algorithm].
Liang L; Yang MH; Li YF
Guang Pu Xue Yu Guang Pu Fen Xi; 2010 Oct; 30(10):2724-8. PubMed ID: 21137408
[TBL] [Abstract][Full Text] [Related]
17. Dimension Reduction Aided Hyperspectral Image Classification with a Small-sized Training Dataset: Experimental Comparisons.
Su J; Yi D; Liu C; Guo L; Chen WH
Sensors (Basel); 2017 Nov; 17(12):. PubMed ID: 29186846
[TBL] [Abstract][Full Text] [Related]
18. A Versatile Deep Learning Architecture for Classification and Label-Free Prediction of Hyperspectral Images.
Manifold B; Men S; Hu R; Fu D
Nat Mach Intell; 2021 Apr; 3():306-315. PubMed ID: 34676358
[TBL] [Abstract][Full Text] [Related]
19. A Novel Extreme Learning Machine Classification Model for e-Nose Application Based on the Multiple Kernel Approach.
Jian Y; Huang D; Yan J; Lu K; Huang Y; Wen T; Zeng T; Zhong S; Xie Q
Sensors (Basel); 2017 Jun; 17(6):. PubMed ID: 28629202
[TBL] [Abstract][Full Text] [Related]
20. Hyperspectral Image Classification for Land Cover Based on an Improved Interval Type-II Fuzzy C-Means Approach.
Huo H; Guo J; Li ZL
Sensors (Basel); 2018 Jan; 18(2):. PubMed ID: 29373548
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
