Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Xintao Du"'
Publikováno v:
PeerJ, Vol 12, p e18036 (2024)
Pesticide spraying is a cost-effective way to control crop pests and diseases. The effectiveness of this method relies on the deposition and distribution of the spray droplets within the targeted application area. There is a critical need for an accu
Externí odkaz:
https://doaj.org/article/f3b5b274408e4369b80fd6647cb20491
Publikováno v:
Frontiers in Immunology, Vol 15 (2024)
BackgroundAllergic rhinitis (AR), a prevalent chronic inflammatory condition triggered by immunoglobulin E (IgE), involves pivotal roles of immune and metabolic factors in its onset and progression. However, the intricacies and uncertainties in clini
Externí odkaz:
https://doaj.org/article/f70da451abb04f118f88601a37ef0430
Publikováno v:
International immunopharmacology. 108
Allergic rhinitis (AR) is the most common inflammatory disorder induced by complex interactions between genetic and environmental factors. Genetic predisposition is the most important factor in the progression of AR. Previous studies have indicated t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::535972edb7d5e9fb775a163ba8202949
https://pubmed.ncbi.nlm.nih.gov/35636076
https://pubmed.ncbi.nlm.nih.gov/35636076
Publikováno v:
Cytokine. 159:156027
Lipoma preferred partner (LPP) polymorphisms are related to immune diseases, but the role of LPP gene in the pathogenesis of allergic rhinitis (AR) is unclear. The current study aimed to explore the contribution of LPP variants to AR susceptibility i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cdd399f068534dc740e0fad89d8f24f2
https://doi.org/10.1016/j.cyto.2022.156027
https://doi.org/10.1016/j.cyto.2022.156027
Publikováno v:
EURASIP Journal on Image and Video Processing, Vol 2020, Iss 1, Pp 1-10 (2020)
Abstract The traditional information hiding is realized by embedding the secret information into the multimedia, but it will inevitably leave the modification mark in the carrier. This paper proposed a new method of coverless information hiding. Firs
Externí odkaz:
https://doaj.org/article/1bc51636b8a043589ef2ebe61fc05f78
Publikováno v:
IEEE Access, Vol 8, Pp 55063-55075 (2020)
The Rich Model of the Gabor filter (referred to as the GFR steganalytic feature) can detect JPEG-adaptive steganography objects. However, feature dimensionality that is too high will lead to too much computation and will correspondingly reduce the de
Externí odkaz:
https://doaj.org/article/3aa5654140ba42db8d3b3c03ba21073b
Publikováno v:
IEEE Access, Vol 8, Pp 25777-25788 (2020)
Image steganography is a technology that hides sensitive information into an image. The traditional image steganography method tends to securely embed secret information in the host image so that the payload capacity is almost ignored and the stegano
Externí odkaz:
https://doaj.org/article/57f40792e5f34904a67020ed3ef53b92
Publikováno v:
IEEE Access, Vol 8, Pp 195253-195262 (2020)
In terms of payload capacity and visual effects, the existing image steganography technology based on deep neural networks still needs improvement, to solve this problem, this article proposes a new deep convolutional steganography network based on t
Externí odkaz:
https://doaj.org/article/99fec422d2b44aa7bb749a034316931e
Publikováno v:
IEEE Access, Vol 8, Pp 170174-170182 (2020)
Aiming at the problem that the traditional steganography based on carrier modification has the low steganographic capacity, a steganographic scheme based on Fully Convolutional Dense Connection Network (FC-DenseNet) is proposed. Since FC-DenseNet can
Externí odkaz:
https://doaj.org/article/604ddf5e0df64726a317c50281238675
Publikováno v:
IEEE Access, Vol 7, Pp 45460-45471 (2019)
This paper proposes an efficient scheme for generating image hashing by combining the local texture and color angle features. During the stage of texture extraction, using Weber's Law, the difference ratios between the center pixels and their surroun
Externí odkaz:
https://doaj.org/article/817d8f7efcac478f894d090686e73f08