Hyperspectral Imaging Seminar
NOTE: Please send requests for lectures starting
from 21:00 on Wednesday (1 May 2024).
Emails arriving before 21:00 will not be
considered.
Send at least 3 choices in order of
preference. Shortlist of lectures can be found here.
Send requests by email to
hagit@cs.haifa.ac.il
IMPORTANT: list the NUMBER + NAME of
lecture (preferably pairs).
Course Homepage:
http://cs.haifa.ac.il/hagit/courses/seminars/Hyperspectral/Hyperspectral.html
NO LESSONS: 22/5, 12/6, 26/6
General Reference:
See Intro Refs.
Lecture 1 Introduction What is
Hyperspectral Imaging (8/5/24a)
·
Introduction to Hyperspectral Image Analysis
Peg Shippert, Ph.D., Earth Science Applications Specialist, Research Systems,
Inc.
https://ohioopen.library.ohio.edu/cgi/viewcontent.cgi?article=1068&context=spacejournal
·
Intro to Hyperspectral Imaging
https://www.microimages.com/documentation/Tutorials/hyprspec.pdf
·
Multispectral vs Hyperspectral Imagery Explained
https://gisgeography.com/multispectral-vs-hyperspectral-imagery-explained/
Lecture 2
Display of Hyperspectral Images on RGB Displays (8/5/24b)
Color Display for Hyperspectral Imagery
Qian Du, Shangshu Cai and Robert J. Moorhead,
IEEE Trans. On Geoscience and Remote Sensing, Vol 46(6), 2008
http://www.ece.msstate.edu/~du/TGRS-VIS2.pdf
·
A Low-Complexity Approach for Color Display of
Hyperspectral Remote-Sensing Images Using OneBit
Transform Based Band Selection
Begüm Demir, Anıl Çelebi, and Sarp Ertürk
http://kulis.kocaeli.edu.tr/pub/tgrs08_hsidisplay.pdf
·
Design Goals and Solutions for Display of Hyperspectral
Images
Nathaniel P. Jacobson, and Maya R. Gupta
IEEE Trans. On Geoscience and Remote Sensing, Vol 43(11), 2005
http://www.mayagupta.org/publications/JacobsonGuptaTGRS.pdf
·
Linear Fusion of Image Sets for Display
Nathaniel P. Jacobson, Maya R. Gupta and Jeffrey Cole
IEEE Trans. On Geoscience and Remote Sensing, Vol 45(10), 2007
http://www.umbc.edu/rssipl/people/jwang/citation_4.pdf
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4305369
·
Dimensionality Reduction for Useful Display of
Hyperspectral Images
J. Cole
http://jeffcole.org/academics/image_display/image_display.pdf
Lecture 3 Statistics of Hyperspectral
Images (Skip this lecture)
·
Statistics of Real-World Hyperspectral Images
Ayan Chakrabarti and Todd Zickler
Harvard School of Engineering and Applied Sciences
http://vision.seas.harvard.edu/hyperspec/CZ_hss.pdf
·
Principal Component Analysis for Hyperspectral Image Classification.
Surveying and Land Information Science, Journal of the American Congress on
Surveying and Mapping, No. 2, pp.115-122, 2002
Rodarmel, C., Shan, J.
https://engineering.purdue.edu/~jshan/publications/2002/SaLIS_2002_HyperImagesPCA.pdf
·
X On the Statistics of Hyperspectral Imaging Data
Dimitris Manolakis, David Marden, John Kerekes and Gary Shaw
MIT Lincoln Laboratory
https://ritdml.rit.edu/bitstream/handle/1850/3207/JKerekesConfProc04-16-2001.pdf?..
Lecture 4-5 Classification and Target Identification in HI (15/5/24a+15/5/24b)
a) Whole Pixel (ssd/mse)
b) Angle distance
c) Spectral Feature Fitting
d) Sub-Pixel Methods
e) Complete Linear Spectral Unmixing
f) Matched Filtering (partial unmixing)
·
Review in:
Introduction to Hyperspectral Image Analysis
Peg Shippert, Ph.D., Earth Science Applications Specialist, Research Systems,
Inc.
http://spacejournal.ohio.edu/pdf/shippert.pdf
·
Hyperspectral Image Processing for Automatic Target
Detection Applications
Dimitris Manolakis, David Marden, and Gary A. Shaw
MIT Lincoln Laboratory
https://courses.cs.washington.edu/courses/cse591n/07sp/papers/14_1hyperspectralprocessing.pdf
·
A Bayesian Model and Gibbs Sampler for Hyperspectral
Imaging.
Rodriguez-Yam, G., Davis, R.A., and Scharf, L.
Proceedings 2002 IEEE Sensor Array and Multichannel Signal Processing Workshop,
Washington, D.C., 105-109, 2002
http://www.stat.columbia.edu/~rdavis/papers/rodriguezyam844.pdf
·
Unsupervised Unmixing of Hyperspectral Imagery Using the
Constrained Positive Matrix Factorization
Yahya M. Masalmah
https://www.uprm.edu/cise/wp-content/uploads/sites/171/2018/12/masalmahcise.pdf
·
L1 Unmixing and its Application to Hyperspectral Image
Enhancement
Zhaohui Guo, Todd Wittman and Stanley Osher
https://ww3.math.ucla.edu/camreport/cam09-30.pdf
(without the enhancing)
Lecture 6 - Hyperspectral Image Segmentation
(29/5/24a+29/5/24b)
·
Morphological Segmentation of Hyperspectral Images
Guillaume Noyel, Jesus Angulo and Dominique Jeulin
Image Anal Stereol 2007;26:101-109
http://www.ias-iss.org/ojs/IAS/article/viewFile/813/716
·
Hyperspectral image segmentation and unmixing using hidden Markov trees
R Mittelman, AO Hero
Int Conf. Image Processing (ICIP), 2010
http://web.eecs.umich.edu/~hero/Preprints/mittelman_ICIP10.pdf
·
Hyperspectral image segmentation using binary partition trees
S Valero, P Salembier
Int Conf. Image Processing (ICIP), 2011
http://hal.archives-ouvertes.fr/docs/00/57/89/60/PDF/ieee_igarss_10_valero_new.pdf
http://perso.telecom-paristech.fr/~tupin/JTELE/PRES10/Valero.pdf
·
Metric Learning for Hyperspectral Image Segmentation
B. Bue, D. Thompson, M. Gilmore and R. Castaño,
Proc. IEEE WHISPERS 2011. Lisbon, PT., Jun. 2011.
http://www.ece.rice.edu/~bdb1/papers/whispers11_metric.pdf
·
Segmentation and Classification of Hyperspectral Images Using
Minimum Spanning Forest Grown From Automatically Selected Markers
Yuliya Tarabalka, Jocelyn Chanussot,
and Jón Atli Benediktsson
IEEE Transactions on System Man and Cybernetics, Vol 40(5), 2010
http://hal.inria.fr/docs/00/57/88/48/PDF/ieee_trans_10_tara_forest.pdf
·
Object segmentation in hyperspectral images using active contours and
graph cutsSusi Huamán De La Vega &Vidya
Manian
https://www.tandfonline.com/doi/abs/10.1080/01431161.2011.560208
Lecture 7 Hyperspectral Image Denoising
(5/6/24a+5/6/24b)
·
Noise
Reduction in Hyperspectral Imagery: Overview and Application
Behnood Rasti, Paul Scheunders, Pedram Ghamisi, Giorgio Licciardi and Jocelyn Chanussot
Remote Sensing 2018, 10(3), 482
https://www.mdpi.com/2072-4292/10/3/482
·
Denoising
of hyperspectral imagery using principal component analysis and wavelet
shrinkage,
G. Chen and S.-E. Qian,
Geoscience and Remote Sensing, IEEE Transactions on, vol. 49, no. 3, pp.
973980, 2011
https://pdfs.semanticscholar.org/e5d4/43601071344b466e94114b2d528d378c7c1e.pdf
·
Denoising
Hyperspectral Imagery Using Principal Component Analysis and Block-Matching 4D
Filtering
Chen, Guangyi; Bui, Tien D.; Quach, Kha Gia; Qian,
Shen-En
Canadian Journal of Remote Sensing Volume 40, 2014 - Issue 1
·
Spectral
Image Denoising with Cubic Total variation Model
H. Zhang
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information
Sciences, Volume I-7, 2012
http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/I-7/95/2012/isprsannals-I-7-95-2012.pdf
·
Wavelet
Packets for multi- and hyper-spectral imagery
J. J. Benedetto, W. Czaja, M. Ehler, C. Flake, M. Hirn
https://www.researchgate.net/publication/252701859_Wavelet_Packets_for_multi-_and_hyper-spectral_imagery/link/0deec538487175ffc6000000/download?_tp=eyJjb250ZXh0Ijp7ImZpcnN0UGFnZSI6InB1YmxpY2F0aW9uIiwicGFnZSI6InB1YmxpY2F0aW9uIn19
·
Challenging:
Denoising Hyperspectral Imagery and Recovering Junk Bands using Wavelets and
Sparse Approximation
Adam C. Zelinski and Vivek K Goyal
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4241251
Lecture 8 HI Sensor Fusion
(Skip This year)
·
Prediction Accuracy of Color Imagery from Hyperspectral Imagery
Peter Bajcsy and Rob Kooper
https://isda.ncsa.illinois.edu/peter/publications/conferences/2005/PB-20050328-2.pdf
·
Multisensor Fusion with Hyperspectral
Imaging Data: Detection and Classification
Su May Hsu , Hsiao-hua K. Burke
http://www.ll.mit.edu/publications/journal/pdf/vol14_no1/14_1multisensorfusion.pdf
·
Feature Based Fusion of Multisensor
Data-Inclusion of Hyperspectral Data into Classification of High Resolution
Orthophotos
A. Greiwe
http://www.ecognition.com/sites/default/files/290_ggrs2004_greiwe_g273.pdf
·
Too Simple:
Spectral Interpretation Based on Multisensor Fusion
for Urban Mapping
Be΄ata Csath΄o, Toni Schenk
and Suyoung Seo
http://rsl.geology.buffalo.edu/documents/csatho_berlin03_paper.pdf
·
Very Basic:
Comparative Image Fusion Analysais
Firooz Sadjadi
OTCBVS-05
http://www.cse.ohio-state.edu/OTCBVS/05/OTCBVS-05-FINALPAPERS/W01_13.pdf
Lecture 9 HI Compression (skip)
·
Hyperspectral Image Compression Using Three-Dimensional Wavelet Coding
Xaoli Tang, William, A. Pearlman and James W. Modestino
http://www.cipr.rpi.edu/staff/pearlman.html/papers/tgars02_tp.pdf
·
Exploiting Calibration-Induced Artifacts in Lossless Compression of
Hyperspectral Imagery
Aaron B. Kiely, and Matthew A. Klimesh
IEEE Trans. On Geoscience and Remote Sensing, Vol 46(6), 2008
http://compression.jpl.nasa.gov/hyperspectral/KielyKlimesh_HyperArtifacts_preprint.pdf
Lecture 10 Face Recognition in
Hyperspectral images (19/6/24a)
·
Face Recognition in Hyperspectral Images
Zhihong Pan, Glenn Healey, Manish
Prasad, and Bruce Tromberg
IEEE PAMI Vol 25 no 12 2003
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.210.4398&rep=rep1&type=pdf
·
Studies on Hyperspectral Face Recognition in Visible Spectrum with
Feature Band Selection, (Uses PCA)
Wei Di, Lei Zhang, David Zhang, and Quan Pan,
IEEE Transactions on Systems, Man, and Cybernetics Part a: Systems and
Humans,
Volume 40, No.6, 1354-1361, 2010.
·
Hyper spectral face image based biometric recognition (also PCA)
Siddharth B. Dabhade ; Nagsen S. Bansod ; Yogesh S.
Rode ; M. M. Kazi ; K
Int Conf on Global Trends in Signal Processing, Information Computing and
Communication (ICGTSPICC), 2016
·
Illumination Invariant Face Recognition Using Near-Infrared Images (Uses LBP)
Stan Z. Li, RuFeng Chu, ShengCai
Liao, and Lun Zhang
IEEE PAMI Vol 29 no 4, 627 639, 2007
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.137.7331&rep=rep1&type=pdf
·
Towards Hyperspectral Face Recognition, (fusion of Visible and NIR EMS)
Stefan A. Robila,
Proc. SPIE 6812, Image Processing: Algorithms and Systems VI, Volume 6812, 2008
·
Pixel Based Supervised Classification of Hyperspectral Face Images for
Face Recognition
Shwetanka Neeraja Jitendraa
Vikeshb Kamal Jain
Procedia Computer Science Volume 132, Pages 706-717, 2018
https://www.sciencedirect.com/science/article/pii/S1877050918308093
Lecture 11 Hyperspectral image analysis of
skin (Skip this
lecture)
Zonios Papers:
·
Skin Melanin, Hemoglobin, and Light Scattering Properties can be
Quantitatively Assessed In Vivo Using Diffuse Reflectance Spectroscopy
George Zonios, Julie Bykowski, and Nikiforos Kollias
2001
http://www.science.mcmaster.ca/medphys/images/files/graduate/JournalClub/2011-2012/zonios2001.pdf
·
Light scattering spectroscopy of human skin in vivo
George Zonios and Aikaterini Dimou
1999
Only to page 6.
http://www.opticsinfobase.org/vjbo/fulltext.cfm?uri=oe-17-3-1256&id=176052
http://www.opticsinfobase.org/view_article.cfm?gotourl=http%3A%2F%2Fwww%2Eopticsinfobase%2Eorg%2FDirectPDFAccess%2F5220FD0C-AFE7-9FDB-9EB32CB88D71D2D5_176052%2Foe-17-3-1256%2Epdf%3Fda%3D1%26id%3D176052%26seq%3D0%26mobile%3Dno&org=
·
Modeling diffuse reflectance from semi-infinite turbid media:
application to the study of skin optical properties,
G. Zonios and A. Dimou,
Opt. Express 14, 8661-8674 (2006)
http://www.opticsinfobase.org/vjbo/fulltext.cfm?uri=oe-14-19-8661&id=105648
http://www.opticsinfobase.org/view_article.cfm?gotourl=http%3A%2F%2Fwww%2Eopticsinfobase%2Eorg%2FDirectPDFAccess%2F524EEC74-BF62-4435-E9EE2475328176B4_105648%2Foe-14-19-8661%2Epdf%3Fda%3D1%26id%3D105648%26seq%3D0%26mobile%3Dno&org=
·
Melanin absorption spectroscopy: new method for noninvasive skin
investigation and melanoma detection
G Zonios, A Dimou, I Bassukas
Journal of Biomedical Optics 13(1), 2008
http://www.seas.harvard.edu/ekaxiras/pubs/Papers/JBiomOpt_13_014017_2008.pdf
Tsumura Papers:
·
Independent Component Analysis of Skin Color Image
Norimichi Tsumura, Hideaki Haneishi
and Yoichi Miyake
CIC 2006
www.mi.tj.chiba-u.jp/~tsumura/Tsumura/papers/CIC6_ICA.pdf
·
Image-based skin color and texture analysis/synthesis by extracting
hemoglobin and melanin information in the skin
Norimichi Tsumura Nobutoshi Ojima Kayoko Sato
Mitsuhiro Shiraishi
Hideto Shimizu Hirohide Nabeshima Syuuichi Akazaki Kimihiko Hori Yoichi
Miyake
Siggraph 2003
http://www.mi.tj.chiba-u.jp/~tsumura/Tsumura/projects/Siggraph2003/TsumuraSig03.pdf
Yudovsky Papers:
·
Rapid and Accurate Estimation of Blood Saturation, Melanin Content, and
Epidermis Thickness from Spectral Diffuse Reflectance.
D. Yudovsky and L. Pilon
Applied Optics, Vol. 49, no. 10, pp. 17071719, 2010
http://www.seas.ucla.edu/~pilon/Publications/AO2010.pdf
·
Retrieving Skin Properties From In Vivo Diffuse Reflectance
Measurements on Human Skin
D. Yudovsky and L. Pilon
Journal of Biophotonics, Vol. 4, No.5, pp.305-314,
2011
http://www.seas.ucla.edu/~pilon/Publications/JBP2011-1.pdf
·
Liveness detection for iris recognition using multispectral images
Rui Chen, Xirong Lin, Tianhuai
Ding
Pattern Recognition Letters Volume 33, Issue 12, 1 September 2012, Pages
1513-1519
https://www.sciencedirect.com/science/article/abs/pii/S0167865512001262
·
Lecture 12 Biometrics via Hyperspectral
imaging (19/6/24b)
Liveliness
detection (determining live vs fake person)
·
Liveness detection for iris recognition using multispectral images
Rui Chen, Xirong Lin, Tianhuai
Ding
Pattern Recognition Letters Volume 33, Issue 12, 1 September 2012, Pages
1513-1519
https://www.sciencedirect.com/science/article/abs/pii/S0167865512001262
·
Face Liveness Detection by Learning Multispectral Reflectance
Distributions
Zhiwei Zhang, Dong Yi, Zhen Lei, Stan Z. Li
Face and Gesture 2011
https://www.researchgate.net/publication/224238158_Face_liveness_detection_by_learning_multispectral_reflectance_distributions
·
The imaging issue in an automatic face/disguise detection system (2 wavelengths)
Ioannis Pavlidis and Peter Symosek,
Proceedings of IEEE workshop on Computer Vision Beyond the Visible Spectrum:
Methods and Applications, 2000
https://www.cpl.uh.edu/images/publication_files/C13.pdf
·
Masked fake face detection using radiance measurements (2 wavelengths)
Youngshin Kim, Jaekeun Na, Seongbeak Yoon, and Juneho Yi,
Journal of the Optical Society of America A, vol. 26, no. 4, 2009
https://pdfs.semanticscholar.org/6e42/5c9315bf9a4643fb8aa33cd2efaf5a650471.pdf
·
Fingerprint detection skip
Spectroscopically enhanced method and system for
multi-factor biometric authentication.
Davar P, 2008, IEICE Trans Inf Syst E91-D(5):13691379
https://www.jstage.jst.go.jp/article/transinf/E91.D/5/E91.D_5_1369/_pdf
Lecture 13 Emotion and stress detection
using HI (skip)
·
Remote sensing of stress using Electro-optics imaging technique
Yuen, P., Chen, T., Hong, K., Tsitiridis, A.,
Jackman, J., James, D., Richardson,
M. A., Oxford, W., Piper, J., Thomas, F. and Lightman, S.
Proceedings of SPIE - The International Society for Optical Engineering 7486 · September 2009
https://pdfs.semanticscholar.org/c861/ad6178791552fd2b47663a26aeff453cb25a.pdf
·
Biometric study using hyperspectral imaging during stress
Sheela Nagaraj, Shafik Quoraishee, Gabriel Chan, Kenneth R. Short
Proceedings Volume 7674, Smart
Biomedical and Physiological Sensor Technologies VII; 76740K (2010)
·
Detecting Happiness Using Hyperspectral Imaging Technology
Min Hao, Guangyuan Liu, Anu
Gokhale, Ya Xu, and Rui Chen
Computational Intelligence and Neuroscience Volume 2019
https://www.hindawi.com/journals/cin/2019/1965789/
Lecture 14 Medical studies using HI (3.7.24a+3.7.24b)
Medical imaging as well as skin 9melanoma
detection etc)
·
Visible
reflectance hyperspectral imaging: characterization of a noninvasive,
in vivo system for determining tissue perfusion.
Zuzak, K. J., Schaeberle, M. D. and Lewis, E. N.
Anal. Chem., 2002, 74, 20212028.
https://pdfs.semanticscholar.org/d0f8/ae354e09542a13c62a7b4832fe878908229d.pdf
·
Zuzak,
K., Gladwin, M., Cannon, R. and Levin, I.
Imaging hemoglobin oxygen saturation in sickle cell disease patients using
noninvasive visible reflectance hyperspectral techniques: effects of nitric
oxide.
Am. J. Physiol. Heart Circ. Physiol., 2003, 285, H1183H1189.
https://www.semanticscholar.org/paper/Imaging-hemoglobin-oxygen-saturation-in-sickle-cell-Zuzak-Gladwin/26492d5a908940f74ceb7805468ee9bb0cae6c19
·
Differentiation of normal skin and melanoma using high resolution
hyperspectral imaging
Dicker, D.T., Lerner, J., Van Belle, P., Barth, S.F.,
Guerry IV, D., Herlyn, M., Elder, D.E.,
El-Deiry, W.S.
Cancer Biology and Therapy Volume 5, Issue 8, August 2006, Pages 1033-1038
https://www.scopus.com/record/display.uri?eid=2-s2.0-33751195543&origin=inward&txGid=2fd579ccaaa079e889944d86c8ec006b
·
Active DLP Hyperspectral Illumination: A Noninvasive, in Vivo, System
Characterization
Visualizing Tissue Oxygenation at Near Video Rates
Karel J. Zuzak, Robert P. Francis, Eleanor F. Wehner, Maritoni
Litorja, Jeffrey A. Cadeddu,
and Edward H. Livingston
Anal. Chem., 2011, 83 (19), pp 74247430
https://pubs.acs.org/doi/abs/10.1021/ac201467v
·
Characterization of a Near-Infrared Laparoscopic Hyperspectral Imaging
System
for
Minimally Invasive Surgery
Karel J. Zuzak, Sabira C. Naik, George Alexandrakis, Doyle Hawkins, Khosrow
Behbehani, and Edward H. Livingston
Anal. Chem., 2007, 79 (12), pp 47094715
https://pubs.acs.org/doi/pdf/10.1021/ac070367n
·
Medical - Ulcer
http://www.seas.ucla.edu/~pilon/TemporalUlcerDevelopment+Healing.htm
·
Medical - Colon
Lu G., Halig
L., Wang D., Qin X., Chen Z. G., Fei B. Spectral-spatial classification for
noninvasive cancer detection using hyperspectral imaging. Journal of Biomedical Optics . 2014;19(10) doi: 10.1117/1.JBO.19.10.106004.106004
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4183763/
Lecture 16 Art and Hyperspectral images (10/7/24a)
Underpinting, pigment
identification, forgery detection
·
Hyperspectral Imaging for Art
Conservation - See citations within: https://surfaceoptics.com/applications/art-antiquities-conservation-hyperspectral/
·
Chapter 5 Hyperspectral Imaging: A New Technique for the Non-Invasive
Study of Artworks https://www.sciencedirect.com/science/article/abs/pii/S1871173107800078
·
Reflectance Hyperspectral Imaging for Investigation of Works of Art:
Old Master Paintings and Illuminated Manuscripts
https://pubs.acs.org/doi/10.1021/acs.accounts.6b00048
·
Lecture 17 Hyperspectral images -
Applications (10/7/24b )
·
1) Meat Quality
·
2) Opthamology
·
3) Medical - Ulcer
http://www.seas.ucla.edu/~pilon/TemporalUlcerDevelopment+Healing.htm
·
3b) Medical - Colon
Lu G., Halig
L., Wang D., Qin X., Chen Z. G., Fei B. Spectral-spatial classification for
noninvasive cancer detection using hyperspectral imaging. Journal of Biomedical Optics . 2014;19(10) doi: 10.1117/1.JBO.19.10.106004.106004
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4183763/
·
·
4) Vehicle Tracking ??
http://citeseerx.ist.psu.edu/viewdoc/summary?
·
5) Vegetable Monitoring
·
6) Ship Detection
·
7) ancient texts Ancient Greek
text concealed on the back of unrolled papyrus revealed through
shortwave-infrared hyperspectral imaging
https://www.science.org/doi/10.1126/sciadv.aav8936
·
Agriculture:
Hyperspectral image analysis techniques for the
detection and classification of the
early onset of plant disease and stress. Amy Lowe,
Nicola Harrison and Andrew P French,
Plant Methods201713:80
https://plantmethods.biomedcentral.com/articles/10.1186/s13007-017-0233-z#Sec4
Detection of Environmental Change Using Hyperspectral
Remote Sensing
at Olkiluoto Repository
Site, Jyrki Tuominen Tarmo Lipping, 2011
http://www.posiva.fi/files/1502/WR_2011-26_web.pdf
Highly sensitive image-derived indices of
water-stressed plants using hyperspectral
imaging in SWIR and histogram analysis
David M. Kim, Hairong Zhang,
Haiying Zhou, Tommy Du, Qian Wu, Todd C. Mockler
& Mikhail Y. Berezin, Scientific
Reports volume 5, Article number: 15919 (2015)
https://www.nature.com/articles/srep15919
Detecting
and Monitoring Plant Nutrient Stress Using Remote Sensing Approaches: A Review
Chong
Yen Mee, Siva Kumar Balasundram and Ahmad Husni Mohd
Hanif
Asian
Journal of Plant Sciences Volume 16 (1): 1-8, 2017 https://scialert.net/fulltextmobile/?doi=ajps.2017.1.8
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Hyperspectral imaging
using Machine Learning / Deep Learning
·
Hyperspectral Image Classification With Deep Learning Models
Xiaofei Yang ;
Yunming Ye ; Xutao Li
; Raymond Y. K. Lau etal
IEEE Transactions on Geoscience and Remote Sensing, Volume: 56 , Issue: 9 , Sept. 2018
https://ieeexplore.ieee.org/document/8340197
·
Deep Feature Extraction and Classification of Hyperspectral Images
Based on
Convolutional Neural Networks
Yushi
Chen, , Hanlu Jiang, Chunyang
Li, Xiuping Jia, Pedram Ghamisi
IEEE Transactions on Geoscience and Remote Sensing, Volume: 54 , Issue: 10 ,
Oct. 2016
https://elib.dlr.de/106352/2/CNN.pdf
·
Hyperspectral Image Classification Using Convolutional Neural Networks
and Multiple
Feature
Learning
Qishuo
Gao, Samsung Lim and Xiuping Jia
Remote Sensing 2018
https://www.mdpi.com/2072-4292/10/2/299
·
Machine learning based hyperspectral image analysis: A survey
Utsav
B. Gewali, Sildomar T.
Monteiro, Eli Saber
https://arxiv.org/abs/1802.08701 Feb 2019
·
Convolution Neural Network Based on Two-Dimensional Spectrum for
Hyperspectral Image Classification
Hongmin Gao,1 Shuo Lin,1 Yao Yang,1 Chenming Li,1 and
Mingxiang Yang2
https://www.hindawi.com/journals/js/2018/8602103/
·
Signoroni A., Savardi M., Baronio A., Benini S. Deep learning meets hyperspectral
image analysis: a multidisciplinary review. Journal of Imaging . 2019;5:p. 52. doi: 10.3390/jimaging5050052.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8320953/
·