Zobrazeno 1 - 10
of 78
pro vyhledávání: '"Guangyuan Fu"'
Publikováno v:
IET Image Processing, Vol 15, Iss 11, Pp 2656-2665 (2021)
Abstract Single hyperspectral image (HSI) super‐resolution (SR) has attracted researcher's attention; however, most existing methods directly model the mapping between low‐ and high‐resolution images from an external training dataset, which req
Externí odkaz:
https://doaj.org/article/f5f492cacb024e208a447e932fc8f16e
Publikováno v:
IEEE Access, Vol 9, Pp 565-580 (2021)
Class imbalance problems, developed due to the sampling bias or measurement error, occur frequently in real-world pattern classification tasks. The traditional classifiers focus on the overall classification accuracy and ignore the minority class, wh
Externí odkaz:
https://doaj.org/article/1e27511165934faf887ef1ab83b1188b
Publikováno v:
International Journal of Optics, Vol 2021 (2021)
Blind deblurring of a single infrared image is a challenging computer vision problem. Because the blur is not only caused by the motion of different objects but also by the relative motion and jitter of cameras, there is a change of scene depth. In t
Externí odkaz:
https://doaj.org/article/fbe4237c05254c68bcfb02b382114d56
Publikováno v:
International Journal of Digital Multimedia Broadcasting, Vol 2021 (2021)
The convolutional neural network has achieved good results in the superresolution reconstruction of single-frame images. However, due to the shortcomings of infrared images such as lack of details, poor contrast, and blurred edges, superresolution re
Externí odkaz:
https://doaj.org/article/f14c08b1acfb450dba6ae787bd97a2e8
Publikováno v:
Materials, Vol 13, Iss 23, p 5463 (2020)
Previous studies have shown that components with an unequal-walled concrete-filled rectangular hollow section (CFRHS) can achieve a greater resistance under bending than those with equal-walled CFRHS. However, the study on the compressive behavior of
Externí odkaz:
https://doaj.org/article/f43c1b9ef70d4360826d1f93ba91d4d3
Publikováno v:
Computational Intelligence and Neuroscience, Vol 2021 (2021)
Computational Intelligence and Neuroscience
Computational Intelligence and Neuroscience
Extensions of kernel methods for the class imbalance problems have been extensively studied. Although they work well in coping with nonlinear problems, the high computation and memory costs severely limit their application to real-world imbalanced ta
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::97301227a7914d1d79d5dbaf19e8dd84
https://doi.org/10.1155/2021/9911871
https://doi.org/10.1155/2021/9911871
Publikováno v:
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::87ae55d4f82a95ce1cb05ec862167b16
https://doi.org/10.1109/cvpr52688.2022.00470
https://doi.org/10.1109/cvpr52688.2022.00470
Publikováno v:
IET Image Processing. 15:2656-2665
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::23ffe159dde4d0e257284ee1148d6e62
https://doi.org/10.1049/ipr2.12253
https://doi.org/10.1049/ipr2.12253
Publikováno v:
Neurocomputing. 435:53-66
In the field of person re-identification (ReID), multi-branch models are more effective in learning robust features than single-branch models. The current popular multi-branch models are based on ResNet or GoogleNet. These networks are designed initi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e8d0574f8ef2eac10a18310e90029dc4
https://doi.org/10.1016/j.neucom.2020.12.105
https://doi.org/10.1016/j.neucom.2020.12.105
Publikováno v:
Signal, Image and Video Processing. 15:1695-1703
High-resolution is essential to achieve remarkable performance in many applications using hyperspectral images. However, the acquired hyperspectral images are often low-resolution due to the limitations of sensors. Recently, deep learning-based metho
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a28afbd7ae7877a6945a72d5dafca261
https://doi.org/10.1007/s11760-021-01902-9
https://doi.org/10.1007/s11760-021-01902-9