Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Jihun Jeon"'
Autor:
Masahiko Saito, Hiroya Yamada, Kakaraparthi Kranthiraja, Jihun Jeon, Hyung Do Kim, Tsubasa Mikie, Akinori Saeki, Hideo Ohkita, Itaru Osaka
Publikováno v:
Communications Materials, Vol 4, Iss 1, Pp 1-10 (2023)
Abstract In π-conjugated polymers, the amorphous region absent from π–π stacking order typically limits polymer functions compared to the crystalline region with high π–π stacking order. Here, we show that a benzodithiophene–thiazolothiazo
Externí odkaz:
https://doaj.org/article/f5a307bd5e28483588c5b5d8d1f11143
Publikováno v:
IEEE Access, Vol 11, Pp 23505-23516 (2023)
Recent developments in drone technology have led to the widespread use of unmanned aerial vehicles (UAVs). In particular, UAVs are often used in reconnaissance to detect objects such as missing persons in large areas. However, traditional systems use
Externí odkaz:
https://doaj.org/article/c086c1fba0ce463bb2d1ae69ba4cf004
Autor:
Masahiko Saito, Hiroya Yamada, Kakaraparthi Kranthiraja, Jihun Jeon, Hyung Do Kim, Tsubasa Mikie, Akinori Saeki, Hideo Ohkita, Itaru Osaka
Publikováno v:
Communications Materials, Vol 4, Iss 1, Pp 1-1 (2023)
Externí odkaz:
https://doaj.org/article/54b9044a925542039fa514a382f3e65c
Publikováno v:
IEEE Access, Vol 10, Pp 70840-70849 (2022)
Recently, convolutional neural networks (CNNs), which exhibit excellent performance in the field of computer vision, have been in the spotlight. However, as the networks become wider for higher accuracy, the number of parameters and the computational
Externí odkaz:
https://doaj.org/article/22d11f616efe4e8fa33d0e359d30c3aa
Publikováno v:
Applied Sciences, Vol 13, Iss 7, p 4430 (2023)
This study aimed to develop a deep neural network model for predicting the soil water content and bulk density of soil based on features extracted from in situ soil surface images. Soil surface images were acquired using a Canon EOS 100d camera. The
Externí odkaz:
https://doaj.org/article/e7f9f0bd95dc4944be40f18b20d07c02
Publikováno v:
Applied Sciences, Vol 13, Iss 5, p 2936 (2023)
For appropriate managing fields and crops, it is essential to understand soil properties. There are drawbacks to the conventional methods currently used for collecting a large amount of data from agricultural lands. Convolutional neural network is a
Externí odkaz:
https://doaj.org/article/805f086ea7424dd1bd26d32671184d11
Publikováno v:
Advances in Civil Engineering, Vol 2019 (2019)
The objective of this study is to monitor the water content of soil quickly and accurately using a UAV. Because UAVs have higher spatial and temporal resolution than satellites, they are currently becoming more useful in remote sensing areas. We deve
Externí odkaz:
https://doaj.org/article/59ba677261f74befacb3540829b4a9c5
Autor:
Satoshi Kamimura, Masahiko Saito, Yoshikazu Teshima, Kodai Yamanak, Hiroyuki Ichikawa, Ai Sugie, Hiroyuki Yoshida, Jihun Jeon, Hyung Do Kim, Hideo Ohkita, Tsubasa Mikie, Itaru Osaka
Publikováno v:
Chemical Science; 5/7/2024, Vol. 15 Issue 17, p6349-6362, 14p
Publikováno v:
Journal of the Institute of Electronics and Information Engineers. 59:69-77
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b75f5afa07076af171c772249d3c1e99
https://doi.org/10.5573/ieie.2022.59.3.69
https://doi.org/10.5573/ieie.2022.59.3.69
Publikováno v:
Paddy and Water Environment. 20:277-286
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3c6aa4f524eb04bce5800e01f38941ad
https://doi.org/10.1007/s10333-022-00893-8
https://doi.org/10.1007/s10333-022-00893-8