Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Chun-Nan Chou"'
Autor:
Chun-Nan Chou, 周俊男
98
Since the computers and the network is invented, it has made the information burst age, in particular, any information that is absorbed by persons or organizations what they needed is available through the network available, and form useful k
Since the computers and the network is invented, it has made the information burst age, in particular, any information that is absorbed by persons or organizations what they needed is available through the network available, and form useful k
Externí odkaz:
http://ndltd.ncl.edu.tw/handle/54778447684962473418
Autor:
Chun-Nan Chou, 周俊男
95
Banana samples with mosaic symptoms were collected from southern Taiwan, and 12 type isolates of Cucumber mosaic cucumovirus associated with banana mosaic disease were established. The 12 CMV isolates were characterized into three types, (I-I
Banana samples with mosaic symptoms were collected from southern Taiwan, and 12 type isolates of Cucumber mosaic cucumovirus associated with banana mosaic disease were established. The 12 CMV isolates were characterized into three types, (I-I
Externí odkaz:
http://ndltd.ncl.edu.tw/handle/99481844049366127120
Autor:
Chun-Nan Chou, 周俊男
95
This thesis is focused on developing a rectifier and inverter structure for a grid-connected solar photovoltaic (PV) system. The three-armed type of rectifier and inverter is adopted as the main structure of the system, due to its high effici
This thesis is focused on developing a rectifier and inverter structure for a grid-connected solar photovoltaic (PV) system. The three-armed type of rectifier and inverter is adopted as the main structure of the system, due to its high effici
Externí odkaz:
http://ndltd.ncl.edu.tw/handle/22889665036777427803
Autor:
Ming-Chi Lee, Hsin-Hung Yeh, Chun-Nan Chou, Tsui-Chin Tu, Yi-Shu Chiu, Hsiao-Hsuan Jan, Ho-Ming Chen, Bo-Han Hou, Yuh Tzean
Publikováno v:
Scientific Reports, Vol 9, Iss 1, Pp 1-9 (2019)
Scientific Reports
Scientific Reports
Banana (Musa spp.) is one of the world’s most important staple and cash crops. Despite accumulating genetic and transcriptomic data, low transformation efficiency in agronomically important Musa spp. render translational researches in banana diffic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1d48ca18ac4481febd992b9262ad5c9d
https://doi.org/10.1038/s41598-019-47962-3
https://doi.org/10.1038/s41598-019-47962-3
Publikováno v:
Big Data Analytics for Large-Scale Multimedia Search ISBN: 9781119376996
Big Data Analytics for Large-Scale Multimedia Search
Big Data Analytics for Large-Scale Multimedia Search
Deep learning owes its success to three key factors: scale of data, enhanced models to learn representations from data, and scale of computation. This book chapter presented the importance of the data-driven approach to learn good representations fro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f3c0ccda60cd1bcb032b6fff098e4f7d
https://doi.org/10.1002/9781119376996.ch1
https://doi.org/10.1002/9781119376996.ch1
Publikováno v:
MIPR
Deep Learning techniques have achieved remarkable results in many domains. Often, training deep learning models requires large datasets, which may require sensitive information to be uploaded to the cloud to accelerate training. To adequately protect
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::057202106e437fc893c6dbcbb5bc18fa
https://doi.org/10.1109/mipr.2019.00068
https://doi.org/10.1109/mipr.2019.00068
Publikováno v:
MIPR
This paper addresses the challenges of small training data in deep learning. We share our experiences in the medical domain and present promises and limitations. In particular, we show through experimental results that GANs are ineffective in generat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::75a5cd863e586842e503ae4a6d811ac9
https://doi.org/10.1109/mipr.2019.00022
https://doi.org/10.1109/mipr.2019.00022
Publikováno v:
CVPR
In this paper we propose the macroblock scaling (MBS) algorithm, which can be applied to various CNN architectures to reduce their model size. MBS adaptively reduces each CNN macroblock depending on its information redundancy measured by our proposed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ea942ffb7d6651b818e8bed98427399b
http://arxiv.org/abs/1809.06569
http://arxiv.org/abs/1809.06569
Publikováno v:
AIVR
This paper proposes BRIEF, a backward reduction algorithm that explores compact CNN-model designs from the information flow perspective. This algorithm can remove substantial non-zero weighting parameters (redundant neural channels) of a network by c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e4949065b8f1e003f10b72159c370147
http://arxiv.org/abs/1807.05726
http://arxiv.org/abs/1807.05726