Zobrazeno 1 - 10
of 38
pro vyhledávání: '"Maozhong Fu"'
Autor:
Wei Wang, Yi Shi, Fang He, Donghui Fang, Jia Gan, Fuqiu Wu, Yueda AG, Xiaodong Deng, Qi Cao, Chu Duo, Wangdeng RZ, Maozhong Fu, Jun Yi
Publikováno v:
Animals, Vol 12, Iss 23, p 3239 (2022)
In aiming to achieve sustainable development goals in the livestock industry, it is becoming increasingly necessary and important for the effective conservation of genetic resources. There are some indigenous cattle breeds in Sichuan, southwest China
Externí odkaz:
https://doaj.org/article/9bb9a7d108ff4379bc930deac43c1911
Publikováno v:
Sensors, Vol 21, Iss 6, p 1951 (2021)
The progress brought by the deep learning technology over the last decade has inspired many research domains, such as radar signal processing, speech and audio recognition, etc., to apply it to their respective problems. Most of the prominent deep le
Externí odkaz:
https://doaj.org/article/8fcd183d810449589d3c9bfe8faffe7c
Publikováno v:
PLoS ONE, Vol 13, Iss 8, p e0201534 (2018)
Indigenous cattle in Sichuan Province, southwestern China, provide abundant genetic resources. However, their genetic diversity and population structure remain largely unknown, especially on the genome-wide scale. In the present study, we successfull
Externí odkaz:
https://doaj.org/article/435215df9b09496290af00bc8093a6ac
Publikováno v:
PLoS ONE, Vol 12, Iss 3, p e0174299 (2017)
The hog deer (Axis porcinus) is a small deer whose natural habitat is the wet or moist tall grasslands in South and Southeast Asia. Wild populations have dramatically decreased in recent decades. While wild hog deer were recently acknowledged to be e
Externí odkaz:
https://doaj.org/article/3332b7b78d3c49a9800327b6d43eb8e3
Publikováno v:
PLoS ONE, Vol 12, Iss 10, p e0186862 (2017)
The polled phenotype of cattle is increasingly becoming favourable mainly because of the enhanced emphasis on animal welfare, for which the causative mutations have been reported during the past years. The Shuxuan cattle are a new synthetic breed by
Externí odkaz:
https://doaj.org/article/5f9f6a5439c545b691c0feb75a4ecd45
Publikováno v:
Journal of Electrical and Computer Engineering, Vol 2015 (2015)
A novel method for solving Doppler ambiguous problem based on compressed sensing (CS) theory is proposed in this paper. A pulse train with the random and sparse transmitting time is transmitted. The received signals after matched filtering can be vie
Externí odkaz:
https://doaj.org/article/9bdca9b29ad04eb2b3dc96683b3d31a2
Publikováno v:
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::73b27483a2ee4a645d9a1e5a26240a48
https://doi.org/10.1109/icassp49357.2023.10094669
https://doi.org/10.1109/icassp49357.2023.10094669
Publikováno v:
IEEE Sensors Journal. 22:4268-4280
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::78d8cbb84127e74eec4415514437bedd
https://doi.org/10.1109/jsen.2022.3141879
https://doi.org/10.1109/jsen.2022.3141879
Publikováno v:
Future Generation Computer Systems. 125:206-220
Deep neural network (DNN) has been widely applied in many fields of artificial intelligence (AI), gaining great popularity both in industry and academia. Increasing the size of DNN models does dramatically improve the learning accuracy. However, trai
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cb57b76fc01b2d752adebfcd31989993
https://doi.org/10.1016/j.future.2021.06.021
https://doi.org/10.1016/j.future.2021.06.021
Publikováno v:
IEEE Transactions on Aerospace and Electronic Systems. 57:968-983
Amplitude comparison monopulse systems encounter the target resolution problem when multiple targets occupy the same range-azimuth cell. To solve this problem, a new angle estimation approach is proposed. The traditional range-cell-based signal proce
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::288e168b96d9e2c62f21d1e58cc146c6
https://doi.org/10.1109/taes.2020.3035434
https://doi.org/10.1109/taes.2020.3035434