Zobrazeno 1 - 10
of 18
pro vyhledávání: '"guangjie kou"'
Publikováno v:
Information Processing in Agriculture, Vol 8, Iss 3, Pp 437-445 (2021)
It is of great significance to use underwater video and image processing technology to detect and analyze fish behaviors. In this paper, an Oplegnathus image dataset for fish behaviors study by deep learning algorithm is constructed, and the data is
Externí odkaz:
https://doaj.org/article/cde3dfd945454aaaa126dfc4e9a9f7b8
Publikováno v:
IEEE Access, Vol 8, Pp 127631-127639 (2020)
Nonlinear vibration plays a vital role in ultrasonic infrared thermography testing due to contact-collision effect between a horn and sample, and the effects of contact roughness and sample mass on vibration characteristics of a horn-sample system ar
Externí odkaz:
https://doaj.org/article/4d3ca823fa354f648e4043ae716bd641
Publikováno v:
Photonic Sensors, Vol 9, Iss 2, Pp 142-150 (2019)
Abstract Aiming at the drawbacks of low contrast and high noise in the thermal images, a novel method based on the combination of the thermal image sequence reconstruction and the first-order differential processing is proposed in this work, which is
Externí odkaz:
https://doaj.org/article/c8bc796d0b324825899b6fa941e99689
SAR Image Invariant Feature Extraction by Anisotropic Diffusion and Multi-Gray Level Simplified PCNN
Publikováno v:
IEEE Access, Vol 7, Pp 47135-47142 (2019)
Besides the target in synthetic aperture radar (SAR) image, the structural information remained in speckle and shadow is also very important when we extract the invariant feature of SAR image. However, the output of the classical pulse coupled neural
Externí odkaz:
https://doaj.org/article/62ecdd25f1c84f0f9f71d5013813b8fd
Publikováno v:
IEEE Access, Vol 7, Pp 149649-149656 (2019)
Topological invariant features take priority over other vision features in early visual perception stage, which is the core idea of topological perception theory. In order to improve the robustness and distinguishability of the invariant features ext
Externí odkaz:
https://doaj.org/article/fee83c548c4344ff9e52bf40ef632aa1
Publikováno v:
International Conference on Signal Processing and Communication Technology (SPCT 2022).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ff2030f3b453dd4592ca42e10048a5f8
https://doi.org/10.1117/12.2673939
https://doi.org/10.1117/12.2673939
Publikováno v:
IEEE Geoscience and Remote Sensing Letters. 18:1650-1654
Object detection in remote sensing images has important applications in various aspects. Object detection algorithms with deep convolutional neural networks (DCNNs) have made remarkable progress. However, when processing objects on vastly multiple sc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bedb25b721dc6a94bd97751128bf5956
https://doi.org/10.1109/lgrs.2020.3004061
https://doi.org/10.1109/lgrs.2020.3004061
Publikováno v:
Information Processing in Agriculture, Vol 8, Iss 3, Pp 437-445 (2021)
It is of great significance to use underwater video and image processing technology to detect and analyze fish behaviors. In this paper, an Oplegnathus image dataset for fish behaviors study by deep learning algorithm is constructed, and the data is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::84f325aa5c732d1853a030ff1b92fb7b
https://doi.org/10.1016/j.inpa.2020.10.001
https://doi.org/10.1016/j.inpa.2020.10.001
Publikováno v:
Journal of Reinforced Plastics and Composites. :073168442311628
This paper proposes a new algorithm to generate representative volume elements (RVEs) with random fiber distribution in fiber reinforced composites (FRC). The proposed algorithm is straightforward and easy to implement based on judging the maximum an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3556d6da0f621b7a941bacbdc45603f5
https://doi.org/10.1177/07316844231162808
https://doi.org/10.1177/07316844231162808
Publikováno v:
Materials Today Communications. 34:105072
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::484634d93ff245a2899823235cfea0f5
https://doi.org/10.1016/j.mtcomm.2022.105072
https://doi.org/10.1016/j.mtcomm.2022.105072