Zobrazeno 1 - 10
of 46
pro vyhledávání: '"Jianhang Zhang"'
Publikováno v:
International Journal of Digital Earth, Vol 17, Iss 1 (2024)
ABSTRACTQuick and accurate extraction of un-collapsed buildings from post-disaster High-resolution Remote Sensing Images (HRSIs) is imperative for emergency response. Pre-disaster HRSIs could serve as auxiliary data for training models to expedite th
Externí odkaz:
https://doaj.org/article/721d6f5a553e4453b0741d6801d7e186
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 17998-18011 (2024)
Water vapor is a critical parameter in the earth's climate system, affecting precipitation and global warming. Precipitable water vapor (PWV) is a measure of atmospheric water vapor content that can be obtained by multiple methods. In this study, we
Externí odkaz:
https://doaj.org/article/924a7cb0981c45928bb60f39c6f55294
Autor:
Lili Wang, Huan He, Jiayin Wang, Zhuang Meng, Lei Wang, Xiang Jin, Jianhang Zhang, Pingping Du, Liyu Zhang, Fei Wang, Hongbin Li, Quanliang Xie
Publikováno v:
Plants, Vol 13, Iss 19, p 2788 (2024)
Taraxacum kok-saghyz Rodin (TKS) is a recognized alternative source of natural rubber comparable to the rubber tree. The geranylgeranyl pyrophosphate synthase (GGPS) catalyzed the synthesis of geranylgeranyl pyrophosphate (GGPP), which is an importan
Externí odkaz:
https://doaj.org/article/069d0eae77994151857444708a4371da
Publikováno v:
Frontiers in Plant Science, Vol 15 (2024)
The Ficus erecta complex, characterized by its morphological diversity and frequent interspecific overlap, shares pollinating fig wasps among several species. This attribute, coupled with its intricate phylogenetic relationships, establishes it as an
Externí odkaz:
https://doaj.org/article/2262aa78c48945119daa060d627e9ec4
Autor:
Haobin Xia, Jianjun Wu, Jiaqi Yao, Nan Xu, Xiaoming Gao, Yubin Liang, Jianhua Yang, Jianhang Zhang, Liang Gao, Weiqi Jin, Bowen Ni
Publikováno v:
Land, Vol 13, Iss 8, p 1120 (2024)
Building height is a crucial indicator when studying urban environments and human activities, necessitating accurate, large-scale, and fine-resolution calculations. However, mainstream machine learning-based methods for inferring building heights fac
Externí odkaz:
https://doaj.org/article/25b39e2d82444231837c2e6b6c7653a6
Publikováno v:
Sensors, Vol 23, Iss 21, p 8758 (2023)
This paper proposes a portable wireless transmission system for the multi-channel acquisition of surface electromyography (EMG) signals. Because EMG signals have great application value in psychotherapy and human–computer interaction, this system i
Externí odkaz:
https://doaj.org/article/25b5e30b1f4843e2b0440d6bc8037431
Publikováno v:
Viruses, Vol 15, Iss 2, p 510 (2023)
Geminiviruses are the largest family of plant viruses that cause severe diseases and devastating yield losses of economically important crops worldwide. In response to geminivirus infection, plants have evolved ingenious defense mechanisms to diminis
Externí odkaz:
https://doaj.org/article/ca568ea0b0ca4011a6e569928dbe8bb2
Publikováno v:
International Journal of Molecular Sciences, Vol 23, Iss 14, p 7794 (2022)
Air space-type variegation is the most diverse among the species of known variegated leaf plants and is caused by conspicuous intercellular spaces between the epidermal and palisade cells and among the palisade cells at non-green areas. Trifolium pra
Externí odkaz:
https://doaj.org/article/b297794605c44170a0a751214c43c762
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-1 (2021)
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Externí odkaz:
https://doaj.org/article/e578ff7d7a734f85982edc26bea90375
Publikováno v:
Sensors, Vol 21, Iss 3, p 960 (2021)
In this paper, a transmission-guided lightweight neural network called TGL-Net is proposed for efficient image dehazing. Unlike most current dehazing methods that produce simulated transmission maps from depth data and haze-free images, in the propos
Externí odkaz:
https://doaj.org/article/4f605f4415334897a40e8923be990372