Zobrazeno 1 - 10
of 39
pro vyhledávání: '"Jinliang Yao"'
Publikováno v:
IET Image Processing, Vol 17, Iss 9, Pp 2748-2763 (2023)
Abstract Content‐based image retrieval (CBIR) is the problem of searching for items in an image database that are similar to the query image. Most of the existing image retrieval methods are trained based on metric learning loss functions (e.g. con
Externí odkaz:
https://doaj.org/article/8635915b7425460e9a343e7d8bd05b8b
Autor:
Jinliang Yao, Haonan Zheng
Publikováno v:
IEEE Access, Vol 11, Pp 88451-88461 (2023)
Image-based virtual try-on provides customers with convenient online clothes selections by transferring garments onto a reference person. Despite the emergence of several solutions to generate photo-realistic images and adapt to complex poses, contro
Externí odkaz:
https://doaj.org/article/e7d104471d5643758b2ba53c4703764d
Publikováno v:
IEEE Access, Vol 11, Pp 53249-53261 (2023)
Precipitation nowcasting is very important for the sectors which critically depend on timely and accurate weather information. One of the challenges of precipitation nowcasting is radar echo extrapolation which predicts the radar echo images accurate
Externí odkaz:
https://doaj.org/article/c673c99a7e4946c094d87db186f4a4a9
Publikováno v:
PLoS ONE, Vol 18, Iss 10, p e0286821 (2023)
As a result of climate change and rapid urbanization, urban waterlogging commonly caused by rainstorm, is becoming more frequent and more severe in developing countries. Urban waterlogging sometimes results in significant financial losses as well as
Externí odkaz:
https://doaj.org/article/6f42a9b00eda46718fcd0f447303a295
Publikováno v:
IEEE Access, Vol 8, Pp 140250-140260 (2020)
Invariance against rotation of 3D objects is one of the essential properties for 3D shape analysis. Recently proposed algorithms have achieved rotationally invariant 3D point set analysis by using inherently rotation-invariant 3D shape features, i.e.
Externí odkaz:
https://doaj.org/article/865353c6c58147589f50b1510b033c69
Publikováno v:
Journal of Spectroscopy, Vol 2022 (2022)
Soluble solids content (SSC) is a vital evaluation index for the internal quality of apples, and NIR spectroscopy is the preferred technique for predicting the SSC of apples. Due to the differences in fruits’ sizes, their SSC prediction models have
Externí odkaz:
https://doaj.org/article/237eb056cd1242b1bf31a4e8187e36f5
Publikováno v:
Atmosphere, Vol 13, Iss 12, p 2112 (2022)
In this study, a deep learning method called Lightning-SN was developed and used for cloud-to-ground (CG) lightning identification. Based on artificial scenarios, this network model selects radar products that exhibit characteristic factors closely r
Externí odkaz:
https://doaj.org/article/1b048aab98f743279871f1cab9c1c437
Publikováno v:
IEEE Access, Vol 7, Pp 107695-107698 (2019)
The local thunderstorms and gale weather occurring frequently has brought huge losses to the agriculture and transportation industries. This paper presents a method of forecasting the local thunderstorms and gale weather, in which a multisource convo
Externí odkaz:
https://doaj.org/article/576fb848042f4dd1ac9cd72303c7b480
Publikováno v:
Foods, Vol 11, Iss 13, p 1923 (2022)
The transmission spectrum of apples is affected by the fruit’s size, which leads to poor prediction performance of the soluble solids content (SSC) models built for their different apple sizes. In this paper, three sets of near infrared (NIR) spect
Externí odkaz:
https://doaj.org/article/7990b3e83c574be99efc1202b1906261
Publikováno v:
Food Quality and Safety. 7
The temperature difference of fruit itself will affect its near infrared spectrum and the accuracy of its soluble solids content (SSC) prediction model. To eliminate the influence of apple temperature difference on the SSC model, a diffuse transmissi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ae83d20a500665607ad48619a2bb3429
https://doi.org/10.1093/fqsafe/fyad002
https://doi.org/10.1093/fqsafe/fyad002