Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Naisen Yang"'
Publikováno v:
IEEE Access, Vol 8, Pp 142393-142403 (2020)
Stochastic gradient descent and other adaptive optimization methods have been proved effective for training deep neural networks. Within each epoch of these methods, the whole training set is involved to train the model. In general, large training da
Externí odkaz:
https://doaj.org/article/14604ff255dd4085a2b94b9237e9d776
Publikováno v:
Remote Sensing, Vol 15, Iss 2, p 358 (2023)
Atmospheric fine particles (PM2.5) have been found to be harmful to the environment and human health. Recently, remote sensing technology and machine learning models have been used to monitor PM2.5 concentrations. Partial dependence plots (PDP) were
Externí odkaz:
https://doaj.org/article/b26444cc54fd421f984cb52244e02b8c
Publikováno v:
Mathematics, Vol 10, Iss 6, p 863 (2022)
In recent years, deep neural networks (DNN) have been widely used in many fields. Lots of effort has been put into training due to their numerous parameters in a deep network. Some complex optimizers with many hyperparameters have been utilized to ac
Externí odkaz:
https://doaj.org/article/a3397dc96d1743a1a143e9a777f90cc0
Autor:
Naisen Yang, Hong Tang
Publikováno v:
Remote Sensing, Vol 13, Iss 14, p 2723 (2021)
Satellite images are always partitioned into regular patches with smaller sizes and then individually fed into deep neural networks (DNNs) for semantic segmentation. The underlying assumption is that these images are independent of one another in ter
Externí odkaz:
https://doaj.org/article/e3ea0034ee43417780130e1f6132db4b
Autor:
Naisen Yang, Hong Tang
Publikováno v:
Remote Sensing, Vol 12, Iss 11, p 1794 (2020)
Modern convolutional neural networks (CNNs) are often trained on pre-set data sets with a fixed size. As for the large-scale applications of satellite images, for example, global or regional mappings, these images are collected incrementally by multi
Externí odkaz:
https://doaj.org/article/96034c388a3147f088178e887badd04b
Publikováno v:
ISPRS Journal of Photogrammetry and Remote Sensing. 195:105-128
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f6a17512c772d5156ca9f480b4fb96dd
https://doi.org/10.1016/j.isprsjprs.2022.11.010
https://doi.org/10.1016/j.isprsjprs.2022.11.010
Publikováno v:
Journal of Earth Science. 33:869-884
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0870add35da36478fa59980349e7f6f0
https://doi.org/10.1007/s12583-021-1560-6
https://doi.org/10.1007/s12583-021-1560-6
Publikováno v:
IEEE Access, Vol 8, Pp 142393-142403 (2020)
Stochastic gradient descent and other adaptive optimization methods have been proved effective for training deep neural networks. Within each epoch of these methods, the whole training set is involved to train the model. In general, large training da
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8ad38b916f420ab359a05bc92ff07689
https://doi.org/10.1109/access.2020.3013621
https://doi.org/10.1109/access.2020.3013621
Autor:
Hong Tang, Naisen Yang
Publikováno v:
Remote Sensing
Volume 12
Issue 11
Pages: 1794
Remote Sensing, Vol 12, Iss 1794, p 1794 (2020)
Volume 12
Issue 11
Pages: 1794
Remote Sensing, Vol 12, Iss 1794, p 1794 (2020)
Modern convolutional neural networks (CNNs) are often trained on pre-set data sets with a fixed size. As for the large-scale applications of satellite images, for example, global or regional mappings, these images are collected incrementally by multi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b89db7a65804a349fbabe620df0ec9e4
Publikováno v:
Remote Sensing of Environment. 269:112828
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::03f855c4536dc488b6bc86c4164c1a2c
https://doi.org/10.1016/j.rse.2021.112828
https://doi.org/10.1016/j.rse.2021.112828