Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Yaqian Long"'
Autor:
Farhan Ullah, Yaqian Long, Irfan Ullah, Rehan Ullah Khan, Salabat Khan, Khalil Khan, Maqbool Khan, Giovanni Pau
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 14-34 (2024)
The deployment of convolutional neural networks (CNNs) to classify hyperspectral images is extensively discussed in the research study. A number of different algorithms and approaches are applied, including 2-D CNN, 3-D CNN, support vector machine (S
Externí odkaz:
https://doaj.org/article/b8187cdd31d542b4a682bed8f1eb8323
Publikováno v:
Biomolecules, Vol 13, Iss 3, p 416 (2023)
Zinc is an indispensable trace element in the human body and plays an important role in regulating normal growth and development. Zinc homeostasis in the central nervous system is closely related to the development of neuroinflammation, and synaptic
Externí odkaz:
https://doaj.org/article/aec51ff0d6874e1a877fabd4307741e3
Autor:
Yaqian Long, Benoit Rivard, Arturo Sanchez-Azofeifa, Russell Greiner, Dominica Harrison, Sen Jia
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 97, Iss , Pp 102286- (2021)
With the emergence of longwave hyperspectral imaging systems, studies are revealing the potential of these data for discriminating tree species. However, few studies have applied statistical methods of band selection to select and characterize featur
Externí odkaz:
https://doaj.org/article/f709ad411d5e41369f32b8c6fa361047
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 84, Iss , Pp 101957- (2020)
The impact of band selection on endmember selection is seldom explored in the analysis of hyperspectral imagery. This study incorporates the N-dimensional Spectral Solid Angle (NSSA) band selection tool into the Spectral-Spatial Endmember Extraction
Externí odkaz:
https://doaj.org/article/d88a89234b104d0ea99ec99f7a6effd2
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 61:1-12
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::871af839677834f9b2f3c8fbddc32108
https://doi.org/10.1109/tgrs.2023.3275146
https://doi.org/10.1109/tgrs.2023.3275146
Autor:
Sen Jia, Meng Xu, Jun Zhou, Qingqing Zhao, Yaqian Long, Jiayue Zhuang, Dingding Tang, Qingquan Li
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 59:10394-10409
Hyperspectral images encompass abundant information and provide unique characteristics for material classification. However, the labeling of training samples can be challenging in hyperspectral image classification. To address this problem, this stud
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::85a0675b756fa2110b731348e9938b9c
https://doi.org/10.1109/tgrs.2020.3048994
https://doi.org/10.1109/tgrs.2020.3048994
Publikováno v:
Proceedings of the 2022 11th International Conference on Computing and Pattern Recognition.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3f192a7ba00bb8d34c37dc50b79e4fc9
https://doi.org/10.1145/3581807.3581822
https://doi.org/10.1145/3581807.3581822
Publikováno v:
Proceedings of the 2022 11th International Conference on Computing and Pattern Recognition.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c5a247a039ee09e294af336ea5eb99e5
https://doi.org/10.1145/3581807.3581843
https://doi.org/10.1145/3581807.3581843
Publikováno v:
International Journal of Applied Earth Observation and Geoinformation. 79:35-47
Selecting a subset of bands from hyperspectral data can improve the discrimination of ground targets because the most distinguishing spectral features are utilized. Targets with similar spectra are particularly challenging for band selection. A band
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aa5d60c2f5687cc3937a5f08cf9acd47
https://doi.org/10.1016/j.jag.2019.03.002
https://doi.org/10.1016/j.jag.2019.03.002
Autor:
Benoit Rivard, Sen Jia, Russell Greiner, Arturo Sanchez-Azofeifa, Dominica Harrison, Yaqian Long
Publikováno v:
International Journal of Applied Earth Observation and Geoinformation. 97:102286
With the emergence of longwave hyperspectral imaging systems, studies are revealing the potential of these data for discriminating tree species. However, few studies have applied statistical methods of band selection to select and characterize featur
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::94b1f31d7733facde5502728cc04c5b0
https://doi.org/10.1016/j.jag.2020.102286
https://doi.org/10.1016/j.jag.2020.102286