Artículos de revistas sobre el tema "HYPER SPECTRAL IMAGE CLASSIFICATION"
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HUANG Hong, 黄. 鸿., 陈美利 CHEN Mei-li, 段宇乐 DUAN Yu-le y 石光耀 SHI Guang-yao. "Hyper-spectral image classification using spatial-spectral manifold reconstruction". Optics and Precision Engineering 26, n.º 7 (2018): 1827–36. http://dx.doi.org/10.3788/ope.20182607.1827.
Texto completoJavadi, P. "USE SATELLITE IMAGES AND IMPROVE THE ACCURACY OF HYPERSPECTRAL IMAGE WITH THE CLASSIFICATION". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-1-W5 (11 de diciembre de 2015): 343–49. http://dx.doi.org/10.5194/isprsarchives-xl-1-w5-343-2015.
Texto completoAlhayani, Bilal y Haci Ilhan. "Hyper spectral Image classification using Dimensionality Reduction Techniques". IJIREEICE 5, n.º 4 (15 de abril de 2017): 71–74. http://dx.doi.org/10.17148/ijireeice.2017.5414.
Texto completoSharif, I. y S. Khare. "Comparative Analysis of Haar and Daubechies Wavelet for Hyper Spectral Image Classification". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-8 (28 de noviembre de 2014): 937–41. http://dx.doi.org/10.5194/isprsarchives-xl-8-937-2014.
Texto completoShanmugapriya, G. y . "An Efficient Spectral Spatial Classification for Hyper Spectral Images". International Journal of Engineering & Technology 7, n.º 3.12 (20 de julio de 2018): 1050. http://dx.doi.org/10.14419/ijet.v7i3.12.17630.
Texto completoBanit', Ibtissam, N. A. ouagua, Mounir Ait Kerroum, Ahmed Hammouch y Driss Aboutajdine. "Band selection by mutual information for hyper-spectral image classification". International Journal of Advanced Intelligence Paradigms 8, n.º 1 (2016): 98. http://dx.doi.org/10.1504/ijaip.2016.074791.
Texto completoTANG Yan-hui, 唐艳慧, 赵鹏 ZHAO Peng y 王承琨 WANG Cheng-kun. "Texture classification algorithm of wood hyper-spectral image based on multi-fractal spectra". Chinese Journal of Liquid Crystals and Displays 34, n.º 12 (2019): 1182–90. http://dx.doi.org/10.3788/yjyxs20193412.1182.
Texto completoLavanya, K., R. Jaya Subalakshmi, T. Tamizharasi, Lydia Jane y Akila Victor. "Unsupervised Unmixing and Segmentation of Hyper Spectral Images Accounting for Soil Fertility". Scalable Computing: Practice and Experience 23, n.º 4 (23 de diciembre de 2022): 291–301. http://dx.doi.org/10.12694/scpe.v23i4.2031.
Texto completoZhang, Tianxiang, Wenxuan Wang, Jing Wang, Yuanxiu Cai, Zhifang Yang y Jiangyun Li. "Hyper-LGNet: Coupling Local and Global Features for Hyperspectral Image Classification". Remote Sensing 14, n.º 20 (20 de octubre de 2022): 5251. http://dx.doi.org/10.3390/rs14205251.
Texto completoLi, Runya y Shenglian Li. "Multimedia Image Data Analysis Based on KNN Algorithm". Computational Intelligence and Neuroscience 2022 (12 de abril de 2022): 1–8. http://dx.doi.org/10.1155/2022/7963603.
Texto completoMunishamaiaha, Kavitha, Senthil Kumar Kannan, DhilipKumar Venkatesan, Michał Jasiński, Filip Novak, Radomir Gono y Zbigniew Leonowicz. "Hyperspectral Image Classification with Deep CNN Using an Enhanced Elephant Herding Optimization for Updating Hyper-Parameters". Electronics 12, n.º 5 (27 de febrero de 2023): 1157. http://dx.doi.org/10.3390/electronics12051157.
Texto completoKavitha, K. y Dr S. Arivazhagan. "A Novel Feature Derivation Technique for SVM based Hyper Spectral Image Classification". International Journal of Computer Applications 1, n.º 15 (25 de febrero de 2010): 27–34. http://dx.doi.org/10.5120/327-496.
Texto completoSegonne, Charlotte, Nathalie Huret, Sébastien Payan, Mathieu Gouhier y Valéry Catoire. "A Spectra Classification Methodology of Hyperspectral Infrared Images for Near Real-Time Estimation of the SO2 Emission Flux from Mount Etna with LARA Radiative Transfer Retrieval Model". Remote Sensing 12, n.º 24 (16 de diciembre de 2020): 4107. http://dx.doi.org/10.3390/rs12244107.
Texto completoMr. B. Naga Rajesh. "Effective Morphological Transformation and Sub-pixel Classification of Clustered Images". International Journal of New Practices in Management and Engineering 8, n.º 01 (31 de marzo de 2019): 08–14. http://dx.doi.org/10.17762/ijnpme.v8i01.74.
Texto completoArumuga Maria Devi, T. y P. Darwin. "Hyper Spectral Fruit Image Classification for Deep Learning Approaches and Neural Network Techniques". International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 30, n.º 03 (junio de 2022): 357–83. http://dx.doi.org/10.1142/s0218488522400116.
Texto completoHohmann, Martin, Damaris Hecht, Benjamin Lengenfelder, Moritz Späth, Florian Klämpfl y Michael Schmidt. "Proof of Principle for Direct Reconstruction of Qualitative Depth Information from Turbid Media by a Single Hyper Spectral Image". Sensors 21, n.º 8 (19 de abril de 2021): 2860. http://dx.doi.org/10.3390/s21082860.
Texto completointo, Mur y Nur Rochmah DPA. "Classification of Hyper spectral Image Using Support Vector Machine and Marker-Controlled Watershed". International Journal of Computer Trends and Technology 27, n.º 2 (25 de septiembre de 2015): 70–75. http://dx.doi.org/10.14445/22312803/ijctt-v27p112.
Texto completoLiu, Q. J., L. H. Jing, L. M. Wang y Q. Z. Lin. "A Method of Particle Swarm Optimized SVM Hyper-spectral Remote Sensing Image Classification". IOP Conference Series: Earth and Environmental Science 17 (18 de marzo de 2014): 012205. http://dx.doi.org/10.1088/1755-1315/17/1/012205.
Texto completoMarwaha, R., A. Kumar, P. L. N. Raju y Y. V. N. Krishna Murthy. "Target detection algorithm for airborne thermal hyperspectral data". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-8 (28 de noviembre de 2014): 827–32. http://dx.doi.org/10.5194/isprsarchives-xl-8-827-2014.
Texto completoGiulietti, Nicola, Silvia Discepolo, Paolo Castellini y Milena Martarelli. "Correction of Substrate Spectral Distortion in Hyper-Spectral Imaging by Neural Network for Blood Stain Characterization". Sensors 22, n.º 19 (27 de septiembre de 2022): 7311. http://dx.doi.org/10.3390/s22197311.
Texto completoKarthikeyan, A., S. Pavithra y P. M. Anu. "Detection and Classification of 2D and 3D Hyper Spectral Image using Enhanced Harris Corner Detector". Scalable Computing: Practice and Experience 21, n.º 1 (19 de marzo de 2020): 93–100. http://dx.doi.org/10.12694/scpe.v21i1.1625.
Texto completoAwad, Mohamad M. y Marco Lauteri. "Self-Organizing Deep Learning (SO-UNet)—A Novel Framework to Classify Urban and Peri-Urban Forests". Sustainability 13, n.º 10 (16 de mayo de 2021): 5548. http://dx.doi.org/10.3390/su13105548.
Texto completoXie, Jiaxing, Jiajun Hua, Shaonan Chen, Peiwen Wu, Peng Gao, Daozong Sun, Zhendong Lyu, Shilei Lyu, Xiuyun Xue y Jianqiang Lu. "HyperSFormer: A Transformer-Based End-to-End Hyperspectral Image Classification Method for Crop Classification". Remote Sensing 15, n.º 14 (11 de julio de 2023): 3491. http://dx.doi.org/10.3390/rs15143491.
Texto completoShaikh, Muhammad Saad, Keyvan Jaferzadeh, Benny Thörnberg y Johan Casselgren. "Calibration of a Hyper-Spectral Imaging System Using a Low-Cost Reference". Sensors 21, n.º 11 (27 de mayo de 2021): 3738. http://dx.doi.org/10.3390/s21113738.
Texto completoHobbs, Steven, Andrew Lambert, Michael J. Ryan, David J. Paull y John Haythorpe. "Appraisal of Low-Cost Pushbroom Hyper-Spectral Sensor Systems for Material Classification in Reflectance". Sensors 21, n.º 13 (27 de junio de 2021): 4398. http://dx.doi.org/10.3390/s21134398.
Texto completoDyson, Jack, Adriano Mancini, Emanuele Frontoni y Primo Zingaretti. "Deep Learning for Soil and Crop Segmentation from Remotely Sensed Data". Remote Sensing 11, n.º 16 (9 de agosto de 2019): 1859. http://dx.doi.org/10.3390/rs11161859.
Texto completoPelletier, Charlotte, Geoffrey Webb y François Petitjean. "Temporal Convolutional Neural Network for the Classification of Satellite Image Time Series". Remote Sensing 11, n.º 5 (4 de marzo de 2019): 523. http://dx.doi.org/10.3390/rs11050523.
Texto completoFan, Yuhai, Yuiqing Wan, Hui Wang, Xingke Yang, Min Liang, Chunjuan Pan, Shaopeng Zhang, Wenbo Wang y Furong Tan. "Application of an airborne hyper-spectral survey system CASI/SASI in the gold-silver-lead-zinc ore district of Huaniushan, Gansu, China". Geologia Croatica 74, n.º 1 (28 de febrero de 2021): 73–83. http://dx.doi.org/10.4154/gc.2021.04.
Texto completoCoppo, Peter, Leandro Chiarantini y Luciano Alparone. "End-to-End Image Simulator for Optical Imaging Systems: Equations and Simulation Examples". Advances in Optical Technologies 2013 (15 de enero de 2013): 1–23. http://dx.doi.org/10.1155/2013/295950.
Texto completoSingh, Suraj Kumar, Shruti Kanga y Sudhanshu. "Assessment of Geospatial Approaches Used for Classification of Crops". International Journal of Mathematical, Engineering and Management Sciences 3, n.º 3 (1 de septiembre de 2018): 271–79. http://dx.doi.org/10.33889/ijmems.2018.3.3-019.
Texto completoAghighi, H., J. Trinder, S. Lim y Y. Tarabalka. "Improved adaptive Markov random field based super-resolution mapping for mangrove tree identification". ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-8 (27 de noviembre de 2014): 61–68. http://dx.doi.org/10.5194/isprsannals-ii-8-61-2014.
Texto completoHuang, Yuancheng, Liangpei Zhang, Pingxiang Li y Yanfei Zhong. "High-resolution hyper-spectral image classification with parts-based feature and morphology profile in urban area". Geo-spatial Information Science 13, n.º 2 (enero de 2010): 111–22. http://dx.doi.org/10.1007/s11806-010-0004-8.
Texto completoWan, Lei, Ma y Cheng. "The Analysis on Similarity of Spectrum Analysis of Landslide and Bareland through Hyper-Spectrum Image Bands". Water 11, n.º 11 (17 de noviembre de 2019): 2414. http://dx.doi.org/10.3390/w11112414.
Texto completoLi, Huo-Yuan y Yong-Feng Qi. "A Hyper spectral Images Classification Method Based on Maximum Scatter Discriminant Analysis". ITM Web of Conferences 7 (2016): 02007. http://dx.doi.org/10.1051/itmconf/20160702007.
Texto completoVoulodimos, A., K. Fokeas, N. Doulamis, A. Doulamis y K. Makantasis. "NOISE-TOLERANT HYPERSPECTRAL IMAGE CLASSIFICATION USING DISCRETE COSINE TRANSFORM AND CONVOLUTIONAL NEURAL NETWORKS". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B2-2020 (14 de agosto de 2020): 1281–87. http://dx.doi.org/10.5194/isprs-archives-xliii-b2-2020-1281-2020.
Texto completoDai, Xiaoai, Xuwei He, Shouheng Guo, Senhao Liu, Fujiang Ji y Huihua Ruan. "Research on hyper-spectral remote sensing image classification by applying stacked de-noising auto-encoders neural network". Multimedia Tools and Applications 80, n.º 14 (15 de marzo de 2021): 21219–39. http://dx.doi.org/10.1007/s11042-021-10735-0.
Texto completoGopal, Narendra y Sivakumar D. "DIMENSIONALITY REDUCTION BASED CLASSIFICATION USING GENERATIVE ADVERSARIAL NETWORKS DATASET GENERATION". ICTACT Journal on Image and Video Processing 13, n.º 01 (1 de agosto de 2022): 2786–90. http://dx.doi.org/10.21917/ijivp.2022.0396.
Texto completoS, Shitharth, Hariprasath Manoharan, Abdulrhman M. Alshareef, Ayman Yafoz, Hassan Alkhiri y Olfat M. Mirza. "Hyper spectral image classifications for monitoring harvests in agriculture using fly optimization algorithm". Computers and Electrical Engineering 103 (octubre de 2022): 108400. http://dx.doi.org/10.1016/j.compeleceng.2022.108400.
Texto completoJinglei, Tang, Miao Ronghui, Zhang Zhiyong, Xin Jing y Wang Dong. "Distance-based separability criterion of ROI in classification of farmland hyper-spectral images". International Journal of Agricultural and Biological Engineering 10, n.º 5 (2017): 177–85. http://dx.doi.org/10.25165/j.ijabe.20171005.2264.
Texto completoVinokurov, V. O., I. A. Matveeva, Y. A. Khristoforova, O. O. Myakinin, I. A. Bratchenko, L. A. Bratchenko, A. A. Moryatov et al. "Neural network classifier of hyperspectral images of skin pathologies". Computer Optics 45, n.º 6 (noviembre de 2021): 879–86. http://dx.doi.org/10.18287/2412-6179-co-832.
Texto completoJamali, A. "A FIT-FOR-PURPOSE ALGORITHM FOR ENVIRONMENTAL MONITORING BASED ON MAXIMUM LIKELIHOOD, SUPPORT VECTOR MACHINE AND RANDOM FOREST". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W7 (1 de marzo de 2019): 25–32. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w7-25-2019.
Texto completoMohammed, Bakhtyar Ahmed y Muzhir Shaban Al-Ani. "Review Research of Medical Image Analysis Using Deep Learning". UHD Journal of Science and Technology 4, n.º 2 (27 de agosto de 2020): 75. http://dx.doi.org/10.21928/uhdjst.v4n2y2020.pp75-90.
Texto completoJohn, C. M. y N. Kavya. "Integration of multispectral satellite and hyperspectral field data for aquatic macrophyte studies". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-8 (28 de noviembre de 2014): 581–88. http://dx.doi.org/10.5194/isprsarchives-xl-8-581-2014.
Texto completoWang, Wenxuan, Leiming Liu, Tianxiang Zhang, Jiachen Shen, Jing Wang y Jiangyun Li. "Hyper-ES2T: Efficient Spatial–Spectral Transformer for the classification of hyperspectral remote sensing images". International Journal of Applied Earth Observation and Geoinformation 113 (septiembre de 2022): 103005. http://dx.doi.org/10.1016/j.jag.2022.103005.
Texto completoHonkavaara, E., R. Näsi, R. Oliveira, N. Viljanen, J. Suomalainen, E. Khoramshahi, T. Hakala et al. "USING MULTITEMPORAL HYPER- AND MULTISPECTRAL UAV IMAGING FOR DETECTING BARK BEETLE INFESTATION ON NORWAY SPRUCE". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2020 (21 de agosto de 2020): 429–34. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2020-429-2020.
Texto completoMalinee, Rachane, Dimitris Stratoulias y Narissara Nuthammachot. "Detection of Oil Palm Disease in Plantations in Krabi Province, Thailand with High Spatial Resolution Satellite Imagery". Agriculture 11, n.º 3 (16 de marzo de 2021): 251. http://dx.doi.org/10.3390/agriculture11030251.
Texto completoNotesco, Weksler y Ben-Dor. "Mineral Classification of Soils Using Hyperspectral Longwave Infrared (LWIR) Ground-Based Data". Remote Sensing 11, n.º 12 (16 de junio de 2019): 1429. http://dx.doi.org/10.3390/rs11121429.
Texto completoIdoughi, Ramzi, Thomas H. G. Vidal, Pierre-Yves Foucher, Marc-André Gagnon y Xavier Briottet. "Background Radiance Estimation for Gas Plume Quantification for Airborne Hyperspectral Thermal Imaging". Journal of Spectroscopy 2016 (2016): 1–17. http://dx.doi.org/10.1155/2016/5428762.
Texto completoGörlich, Florian, Elias Marks, Anne-Katrin Mahlein, Kathrin König, Philipp Lottes y Cyrill Stachniss. "UAV-Based Classification of Cercospora Leaf Spot Using RGB Images". Drones 5, n.º 2 (5 de mayo de 2021): 34. http://dx.doi.org/10.3390/drones5020034.
Texto completoPark, Keunho, Young ki Hong, Gook hwan Kim y Joonwhoan Lee. "Classification of apple leaf conditions in hyper-spectral images for diagnosis of Marssonina blotch using mRMR and deep neural network". Computers and Electronics in Agriculture 148 (mayo de 2018): 179–87. http://dx.doi.org/10.1016/j.compag.2018.02.025.
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