Zobrazeno 1 - 10
of 302
pro vyhledávání: '"Wei-Qi Yan"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024)
Abstract The exponential growth in the number of registered trademarks, coupled with the escalating incidents of trademark infringement, has made the automatic detection of such infractions a crucial area of study in the domain of market regulation.
Externí odkaz:
https://doaj.org/article/d24e6f21bf9444bdae42475492e310ca
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-20 (2024)
Abstract The accurate recognition of apples in complex orchard environments is a fundamental aspect of the operation of automated picking equipment. This paper aims to investigate the influence of dense targets, occlusion, and the natural environment
Externí odkaz:
https://doaj.org/article/851ecc9cbab547f985de1e43d3146fb9
Publikováno v:
Intelligent and Converged Networks, Vol 5, Iss 2, Pp 134-146 (2024)
Video understanding and content boundary detection are vital stages in video recommendation. However, previous content boundary detection methods require collecting information, including location, cast, action, and audio, and if any of these element
Externí odkaz:
https://doaj.org/article/6e14cff682934972bff57da36dfeacbf
Autor:
Zhiyuan Mi, Wei Qi Yan
Publikováno v:
Big Data and Cognitive Computing, Vol 8, Iss 8, p 92 (2024)
In agriculture, the timely and accurate assessment of fruit ripeness is crucial to optimizing harvest planning and reduce waste. In this article, we explore the integration of two cutting-edge deep learning models, YOLOv9 and Swin Transformer, to dev
Externí odkaz:
https://doaj.org/article/c0ea31a344014bcd80ef9eea24bce9d1
Publikováno v:
Applied Sciences, Vol 13, Iss 23, p 12608 (2023)
The rapid growth in Artificial Intelligence (AI) has led to considerable progress in Automated Fact Verification (AFV). This process involves collecting evidence for a statement, assessing its relevance, and predicting its accuracy. Recently, researc
Externí odkaz:
https://doaj.org/article/0dd72b3d27ca48769bf4dcd10bd2ef92
Publikováno v:
Plant Phenomics, Vol 2022 (2022)
Traditional methods used to monitor the aboveground biomass (AGB) and belowground biomass (BGB) of slash pine (Pinus elliottii) rely on on-ground measurements, which are time- and cost-consuming and suited only for small spatial scales. In this paper
Externí odkaz:
https://doaj.org/article/3d0df0938e0f4837bd8552e2dfd2eedd
Autor:
Maryam Doborjeh, Xiaoxu Liu, Zohreh Doborjeh, Yuanyuan Shen, Grant Searchfield, Philip Sanders, Grace Y. Wang, Alexander Sumich, Wei Qi Yan
Publikováno v:
Sensors, Vol 23, Iss 2, p 902 (2023)
Tinnitus is a hearing disorder that is characterized by the perception of sounds in the absence of an external source. Currently, there is no pharmaceutical cure for tinnitus, however, multiple therapies and interventions have been developed that imp
Externí odkaz:
https://doaj.org/article/b8a5005f183d46fe910f480af62b8717
Publikováno v:
Mathematics, Vol 10, Iss 23, p 4441 (2022)
In order to solve various security risks faced by image privacy protection, we propose a 3D cuboid image encryption scheme based on message-encoded controlled alternate quantum walks. Firstly, we calculated the initial parameters of the quantum syste
Externí odkaz:
https://doaj.org/article/6d49304b93ee44a6b93be896356abfd2
Publikováno v:
Multimedia Tools and Applications. 82:21673-21685
Sign language recognition is one of the fundamental ways to assist deaf people to communicate with others. An accurate vision-based sign language recognition system using deep learning is a fundamental goal for many researchers. Deep convolutional ne
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d9ce6acd8b97432819c031132a4eb3b2
https://doi.org/10.1007/s11042-023-14646-0
https://doi.org/10.1007/s11042-023-14646-0
Publikováno v:
IEEE Transactions on Image Processing. 32:2174-2189
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::251c911e6584b1c9ae2a113e58eeea62
https://doi.org/10.1109/tip.2023.3263101
https://doi.org/10.1109/tip.2023.3263101