BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

161 related articles for article (PubMed ID: 36679453)

  • 21. 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]  

  • 22. Unsupervised dimensionality reduction of medical hyperspectral imagery in tensor space.
    Gao H; Wang M; Sun X; Cao X; Li C; Liu Q; Xu P
    Comput Methods Programs Biomed; 2023 Oct; 240():107724. PubMed ID: 37506600
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Convolutional Neural Network Based on Bandwise-Independent Convolution and Hard Thresholding for Hyperspectral Band Selection.
    Feng J; Chen J; Sun Q; Shang R; Cao X; Zhang X; Jiao L
    IEEE Trans Cybern; 2021 Sep; 51(9):4414-4428. PubMed ID: 32598287
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Multi-channel morphological profiles for classification of hyperspectral images using support vector machines.
    Plaza J; Plaza AJ; Barra C
    Sensors (Basel); 2009; 9(1):196-218. PubMed ID: 22389595
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Hyperspectral Image Labeling and Classification Using an Ensemble Semi-Supervised Machine Learning Approach.
    Manian V; Alfaro-Mejía E; Tokars RP
    Sensors (Basel); 2022 Feb; 22(4):. PubMed ID: 35214523
    [TBL] [Abstract][Full Text] [Related]  

  • 26. 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]  

  • 27. [Hyperspectral image classification based on 3-D gabor filter and support vector machines].
    Feng X; Xiao PF; Li Q; Liu XX; Wu XC
    Guang Pu Xue Yu Guang Pu Fen Xi; 2014 Aug; 34(8):2218-24. PubMed ID: 25474965
    [TBL] [Abstract][Full Text] [Related]  

  • 28. New bandwidth selection criterion for Kernel PCA: approach to dimensionality reduction and classification problems.
    Thomas M; De Brabanter K; De Moor B
    BMC Bioinformatics; 2014 May; 15():137. PubMed ID: 24886083
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Multi-source remote sensing image classification based on two-channel densely connected convolutional networks.
    Song H; Yang W; Dai S; Yuan H
    Math Biosci Eng; 2020 Oct; 17(6):7353-7377. PubMed ID: 33378900
    [TBL] [Abstract][Full Text] [Related]  

  • 30. SpaSSA: Superpixelwise Adaptive SSA for Unsupervised Spatial-Spectral Feature Extraction in Hyperspectral Image.
    Sun G; Fu H; Ren J; Zhang A; Zabalza J; Jia X; Zhao H
    IEEE Trans Cybern; 2022 Jul; 52(7):6158-6169. PubMed ID: 34499610
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Multi-scale guided feature extraction and classification algorithm for hyperspectral images.
    Huang S; Lu Y; Wang W; Sun K
    Sci Rep; 2021 Sep; 11(1):18396. PubMed ID: 34526567
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Hyperspectral Image Classification with Optimized Compressed Synergic Deep Convolution Neural Network with Aquila Optimization.
    Subba Reddy T; Harikiran J; Enduri MK; Hajarathaiah K; Almakdi S; Alshehri M; Naveed QN; Rahman MH
    Comput Intell Neurosci; 2022; 2022():6781740. PubMed ID: 35845897
    [TBL] [Abstract][Full Text] [Related]  

  • 33. 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]  

  • 34. Dimensionality Reduction of Hyperspectral Images Based on Improved Spatial-Spectral Weight Manifold Embedding.
    Liu H; Xia K; Li T; Ma J; Owoola E
    Sensors (Basel); 2020 Aug; 20(16):. PubMed ID: 32784692
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Spatial mutual information based hyperspectral band selection for classification.
    Amankwah A
    ScientificWorldJournal; 2015; 2015():630918. PubMed ID: 25918742
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Sea Ice Detection Based on an Improved Similarity Measurement Method Using Hyperspectral Data.
    Han Y; Li J; Zhang Y; Hong Z; Wang J
    Sensors (Basel); 2017 May; 17(5):. PubMed ID: 28505135
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Hyperspectral Meets Optical Flow: Spectral Flow Extraction for Hyperspectral Image Classification.
    Liu B; Sun Y; Yu A; Xue Z; Zuo X
    IEEE Trans Image Process; 2023; 32():5181-5196. PubMed ID: 37698966
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Simultaneous Spectral-Spatial Feature Selection and Extraction for Hyperspectral Images.
    Zhang L; Zhang Q; Du B; Huang X; Tang YY; Tao D
    IEEE Trans Cybern; 2018 Jan; 48(1):16-28. PubMed ID: 28113695
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Joint Learning of Correlation-Constrained Fuzzy Clustering and Discriminative Non-Negative Representation for Hyperspectral Band Selection.
    Li Z; Wang W
    Sensors (Basel); 2023 May; 23(10):. PubMed ID: 37430753
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Feature Selection Based on High Dimensional Model Representation for Hyperspectral Images.
    Taskin G; Kaya H; Bruzzone L
    IEEE Trans Image Process; 2017 Jun; 26(6):2918-2928. PubMed ID: 28358688
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 9.