Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Vu Dong Pham"'
Publikováno v:
IEEE Access, Vol 8, Pp 32727-32736 (2020)
Convolutional neural network (CNN) is a widely used method in solving classification and regression applications in industries, engineering, and science. This study investigates the optimizing capability of a swarm intelligence algorithm named moth f
Externí odkaz:
https://doaj.org/article/5545f454ef3a4ed38f4043e96ea2da9b
Autor:
Quang-Thanh Bui, Quoc-Huy Nguyen, Van Manh Pham, Vu Dong Pham, Mai Hoang Tran, Trang T.H. Tran, Huu Duy Nguyen, Xuan Linh Nguyen, Hai Minh Pham
Publikováno v:
Canadian Journal of Remote Sensing, Vol 45, Iss 1, Pp 42-53 (2019)
In remote sensing, Fuzzy C-Means clustering (FCM) is a robust method in determining membership grades of a pixel belonging to 1 or more classes. This paper proposes a novel approach by using the social spider optimization (SSO) algorithm in solving t
Externí odkaz:
https://doaj.org/article/99f06c1488ae442dacfb7e38a274f333
Autor:
Vu-Dong Pham, Gideon Tetteh, Fabian Thiel, Stefan Erasmi, Marcel Schwieder, David Frantz, Sebastian van der Linden
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 129, Iss , Pp 103867- (2024)
Detailed maps on the spatial and temporal distribution of crops are key for a better understanding of agricultural practices and for food security management. Multi-temporal remote sensing data and deep learning (DL) have been extensively studied for
Externí odkaz:
https://doaj.org/article/22f67dca9c634047b093931faf2449cc
Autor:
Quang-Thanh Bui, Tien-Yin Chou, Thanh-Van Hoang, Yao-Min Fang, Ching-Yun Mu, Pi-Hui Huang, Vu-Dong Pham, Quoc-Huy Nguyen, Do Thi Ngoc Anh, Van-Manh Pham, Michael E. Meadows
Publikováno v:
Remote Sensing, Vol 13, Iss 14, p 2709 (2021)
In regular convolutional neural networks (CNN), fully-connected layers act as classifiers to estimate the probabilities for each instance in classification tasks. The accuracy of CNNs can be improved by replacing fully connected layers with gradient
Externí odkaz:
https://doaj.org/article/7faeac37764c444497b3b0064a14383a
Autor:
Arasumani Muthusamy, Fabian Thiel, Vu Dong Pham, Christina Hellmann, Sebastian van der Linden
Undisturbed peatlands constitute relevant carbon sinks. However, drained or degraded peatlands cause carbon emissions and more than 90 % of the peatlands in Mecklenburg-Western Pomerania, Germany, have been drained. In order to achieve the goals for
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7cc34c874f1a08486367c1e9c9d96ee4
https://doi.org/10.5194/egusphere-egu23-5352
https://doi.org/10.5194/egusphere-egu23-5352
Publikováno v:
Remote Sensing Letters. 12:654-665
Landsat and Sentinel-2 are two freely accessible satellite data that are relevant for global land cover monitoring. However, the uses of the latter data set are growing because of its higher spatia...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f6e858c8fc18e556cb0cc849a90c0130
https://doi.org/10.1080/2150704x.2021.1918789
https://doi.org/10.1080/2150704x.2021.1918789
Akademický článek
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Autor:
Van-Manh Pham, Vu-Dong Pham, Minh Hai Pham, Huu Duy Nguyen, Van Manh Vu, Quang-Thanh Bui, Quoc-Huy Nguyen
Publikováno v:
Remote Sensing Letters. 11:353-362
This study aims at investigating the balance between exploration and exploitation search capability of a newly developed Salp swarm optimization algorithm (SSA) for fine-tuning parameters of a thre...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7597e97047f6a62e631c2b62839336f8
https://doi.org/10.1080/2150704x.2020.1716409
https://doi.org/10.1080/2150704x.2020.1716409
Publikováno v:
IEEE Access. 8:32727-32736
Convolutional neural network (CNN) is a widely used method in solving classification and regression applications in industries, engineering, and science. This study investigates the optimizing capability of a swarm intelligence algorithm named moth f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c49fc16160e9c8156c105f7f7278a7c0
https://doi.org/10.1109/access.2020.2973415
https://doi.org/10.1109/access.2020.2973415
Autor:
Tien-Yin Chou, Ching-Yun Mu, Yao-Min Fang, Quoc-Huy Nguyen, Thanh Van Hoang, Vu-Dong Pham, Pi-Hui Huang, Van-Manh Pham, Do Thi Ngoc Anh, Michael E. Meadows, Quang-Thanh Bui
Publikováno v:
Remote Sensing, Vol 13, Iss 2709, p 2709 (2021)
Remote Sensing; Volume 13; Issue 14; Pages: 2709
Remote Sensing; Volume 13; Issue 14; Pages: 2709
In regular convolutional neural networks (CNN), fully-connected layers act as classifiers to estimate the probabilities for each instance in classification tasks. The accuracy of CNNs can be improved by replacing fully connected layers with gradient
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c6d9293b0044681044cff9d752355c8a
https://doi.org/10.3390/rs13142709
https://doi.org/10.3390/rs13142709