المؤلفون: Koushikey Chhapariya, Emmett Ientilucci, Krishna Mohan Buddhiraju, Anil Kumar

المصدر: Remote Sensing, Vol 16, Iss 24, p 4729 (2024)

مصطلحات موضوعية: multi-platform, hyperspectral imaging, remote sensing, target detection, UAV hyperspectral dataset, CASI dataset, Science

وصف الملف: electronic resource

Relation: https://www.mdpi.com/2072-4292/16/24/4729; https://doaj.org/toc/2072-4292

URL الوصول: https://doaj.org/article/809a41ce17844849a746425af2f7df61

المؤلفون: Xiaojie Xia, Wei Liu, Liuan Wang, Jun Sun

المصدر: IEEE Access, Vol 11, Pp 13152-13162 (2023)

مصطلحات موضوعية: Hyperspectral dataset, food analysis, food ingredient retrieval, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

وصف الملف: electronic resource

Relation: https://ieeexplore.ieee.org/document/10040644/; https://doaj.org/toc/2169-3536

URL الوصول: https://doaj.org/article/d78f8fcfdc3a4d22968832289572a81a

المؤلفون: Zheyong Li, Jinghua Li, Pei Zhang, Lihui Zheng, Yilong Shen, Qi Li, Xin Li, Tong Li

المصدر: Remote Sensing; Volume 15; Issue 4; Pages: 1023

مصطلحات موضوعية: hyperspectral image (HSI), underwater target detection, synthetic data, domain adaptation, hyperspectral dataset

جغرافية الموضوع: agris

وصف الملف: application/pdf

Relation: AI Remote Sensing; https://dx.doi.org/10.3390/rs15041023

الاتاحة: https://doi.org/10.3390/rs15041023

المؤلفون: Emanuele Plebani

مصطلحات موضوعية: Computer vision, Machine learning not elsewhere classified, Probability theory, Cell segmentation, Hyperspectral dataset, semi-supervised segmentation, deep segmentation model, U-Net segmentation networks, Gaussian Mixture Model Classifier, panoptic segmentation

Relation: https://figshare.com/articles/thesis/Unraveling_Complexity_Panoptic_Segmentation_in_Cellular_and_Space_Imagery/25639641

الاتاحة: https://doi.org/10.25394/pgs.25639641.v1

المؤلفون: Sarah Bamford, Wil Gardner, Paul Pigram, Ben Muir, David Winkler, Davide Ballabio

مصطلحات موضوعية: Machine learning, Mathematical sciences, Physical sciences, Other physical sciences, ToF-SIMS hyperspectral imaging data, self-organising map (SOM), surface analysis, machiene learning, inkjet ink, inkjet printing, Hyperspectral dataset

Relation: https://figshare.com/articles/dataset/Data_set_for_a_comprehensive_tutorial_on_the_SOM-RPM_toolbox_for_MATLAB/25648905

الاتاحة: https://doi.org/10.26181/25648905.v1
https://figshare.com/articles/dataset/Data_set_for_a_comprehensive_tutorial_on_the_SOM-RPM_toolbox_for_MATLAB/25648905

المؤلفون: Plebani, Emanuele

المساهمون: Dundar, Murat, Tuceryan, Mihran, Tsechpenakis, Gavriil, Al Hasan, Mohammad

مصطلحات موضوعية: Cell segmentation, Hyperspectral dataset, Semi-supervised segmentation, Deep segmentation model, U-Net segmentation networks, Gaussian Mixture Model Classifier, Panoptic segmentation

وصف الملف: application/pdf

Relation: https://hdl.handle.net/1805/41160

الاتاحة: https://hdl.handle.net/1805/41160

المؤلفون: Xiang Chen, Tao Wang, Shulin Liu, Fei Peng, Atsushi Tsunekawa, Wenping Kang, Zichen Guo, Kun Feng

المصدر: Remote Sensing; Volume 11; Issue 11; Pages: 1286

مصطلحات موضوعية: moss-dominated biological soil crusts (BSCs), random forest (RF) algorithm, in-situ hyperspectral dataset, multispectral remote sensing, Mu Us Sandy Land

جغرافية الموضوع: agris

وصف الملف: application/pdf

Relation: https://dx.doi.org/10.3390/rs11111286

الاتاحة: https://doi.org/10.3390/rs11111286

المؤلفون: Puustinen, Sami, Hyttinen, Joni, Elomaa, Antti-Pekka, Vrzáková, Hana

مصطلحات موضوعية: Medical hyperspectral imaging, Microsurgical training, Tissue classification, Hyperspectral dataset, Human placenta

Relation: https://doi.org/10.1016/j.dib.2023.109526; https://doi.org/10.5281/zenodo.8046363; https://zenodo.org/communities/uef-soc-csi; https://doi.org/10.5281/zenodo.8045939; https://doi.org/10.5281/zenodo.8045940; oai:zenodo.org:8045940

الاتاحة: https://doi.org/10.5281/zenodo.8045940

المؤلفون: AlSuwaidi, A., Grieve, B., Yin, H.

المصدر: AlSuwaidi , A , Grieve , B & Yin , H 2017 , Spectral-texture approach to hyperspectral image analysis for plant classification with SVMs . in 2017 IEEE International Conference on Imaging Systems and Techniques (IST) . pp. 1-6 . https://doi.org/10.1109/IST.2017.8261496

مصطلحات موضوعية: Markov processes, feature extraction, image classification, image texture, support vector machines, Arabidopsis plant, MRF model, Markov random field model, hyperspectral dataset, hyperspectral image analysis, hyperspectral images, plant classification, plant discrimination, plant monitoring, proximal hyperspectral imaging system, spectral texture properties, spectral-texture analysis, spectral-texture approach, Hyperspectral imaging, Imaging, Maximum likelihood estimation, Training, feature selection, markov random field, spectral analysis, texture analysis

وصف الملف: application/pdf

الاتاحة: https://research.manchester.ac.uk/en/publications/bcdff4c5-e48f-4ee1-82d6-62c2b7ad0dcf
https://doi.org/10.1109/IST.2017.8261496
https://pure.manchester.ac.uk/ws/files/66924720/1570378212_2.pdf

المؤلفون: Zichen Guo, Kun Feng, Tao Wang, Shu-Lin Liu, Fei Peng, Atsushi Tsunekawa, Xiang Chen, Wenping Kang

المصدر: Remote Sensing, Vol 11, Iss 11, p 1286 (2019)
Remote Sensing; Volume 11; Issue 11; Pages: 1286

مصطلحات موضوعية: 010504 meteorology & atmospheric sciences, media_common.quotation_subject, Science, Multispectral image, 0211 other engineering and technologies, 02 engineering and technology, 01 natural sciences, Multispectral pattern recognition, in-situ hyperspectral dataset, multispectral remote sensing, 021101 geological & geomatics engineering, 0105 earth and related environmental sciences, media_common, Remote sensing, moss-dominated biological soil crusts (BSCs), Mu Us Sandy Land, random forest (RF) algorithm, Biological soil crust, Hyperspectral imaging, Arid, Random forest, Desertification, General Earth and Planetary Sciences, Environmental science, Satellite

وصف الملف: application/pdf

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d6cbdba8975caac17bc20c13ff2d2220
https://www.mdpi.com/2072-4292/11/11/1286

المؤلفون: Ali AlSuwaidi, Hujun Yin, Bruce Grieve

المصدر: AlSuwaidi, A, Grieve, B & Yin, H 2017, Spectral-texture approach to hyperspectral image analysis for plant classification with SVMs . in 2017 IEEE International Conference on Imaging Systems and Techniques (IST) . pp. 1-6 . https://doi.org/10.1109/IST.2017.8261496

مصطلحات موضوعية: hyperspectral images, Hyperspectral imaging, Computer science, Feature extraction, plant discrimination, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Markov process, Feature selection, 02 engineering and technology, MRF model, 01 natural sciences, support vector machines, markov random field, Imaging, 010309 optics, symbols.namesake, feature selection, Image texture, hyperspectral dataset, 0103 physical sciences, 0202 electrical engineering, electronic engineering, information engineering, hyperspectral image analysis, proximal hyperspectral imaging system, Training, image texture, spectral texture properties, plant classification, spectral-texture approach, texture analysis, spectral-texture analysis, Markov random field, Contextual image classification, business.industry, Markov processes, feature extraction, Markov random field model, Pattern recognition, Arabidopsis plant, Maximum likelihood estimation, plant monitoring, spectral analysis, Support vector machine, symbols, 020201 artificial intelligence & image processing, Artificial intelligence, business, image classification

وصف الملف: application/pdf

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::72476bb8bc98d5c2326365c814789b01
https://doi.org/10.1109/ist.2017.8261496

المؤلفون: Panagiotis Tsakalides, Grigorios Tsagkatakis, Konstantina Fotiadou, Bert Geelen

مصطلحات موضوعية: Hyperspectral Classification, Snapshot Mosaic Images, Hyperspectral Dataset

Relation: https://github.com/kfotiadou/Spectral-Indoors-Classification-Dataset/tree/Spectral_Indoors_Snapshot_Mosaic_Dataset; https://zenodo.org/communities/eu; https://doi.org/; https://doi.org/10.5281/zenodo.546105; oai:zenodo.org:546105

الاتاحة: https://doi.org/10.5281/zenodo.546105

المؤلفون: Emanuele Plebani (18403245)

مصطلحات موضوعية: Computer vision, Machine learning not elsewhere classified, Probability theory, Cell segmentation, Hyperspectral dataset, semi-supervised segmentation, deep segmentation model, U-Net segmentation networks, Gaussian Mixture Model Classifier, panoptic segmentation

Relation: https://figshare.com/articles/thesis/Unraveling_Complexity_Panoptic_Segmentation_in_Cellular_and_Space_Imagery/25639641