Zobrazeno 1 - 10
of 35
pro vyhledávání: '"Mengying Ni"'
Publikováno v:
Remote Sensing, Vol 16, Iss 19, p 3594 (2024)
Semantic segmentation is crucial for a wide range of downstream applications in remote sensing, aiming to classify pixels in remote sensing images (RSIs) at the semantic level. The dramatic variations in grayscale and the stacking of categories withi
Externí odkaz:
https://doaj.org/article/e33db9256b1b4179a3348d841e18223f
Publikováno v:
IET Image Processing, Vol 17, Iss 12, Pp 3616-3629 (2023)
Abstract Image segmentation is pivotal for the understanding of high‐resolution remote sensing images (HRRS). However, because of the inherent uncertainties in remote sensing images and the highly complex resolution of HRRS, ambiguity often occurs
Externí odkaz:
https://doaj.org/article/a91b300e5fea4b29bcefb4ec87885205
Publikováno v:
Applied Sciences, Vol 14, Iss 11, p 4568 (2024)
Show-through phenomena have always been a challenging issue in color-document image processing, which is widely used in various fields such as finance, education, and administration. Existing methods for processing color-document images face challeng
Externí odkaz:
https://doaj.org/article/8b92891d0f1d460499833830478819df
Autor:
Tingting Qu, Jindong Xu, Qianpeng Chong, Zhaowei Liu, Weiqing Yan, Xuan Wang, Yongchao Song, Mengying Ni
Publikováno v:
European Journal of Remote Sensing, Vol 56, Iss 1 (2023)
ABSTRACTRemote sensing image segmentation plays an important role in many industrial-grade image processing applications. However, the problem of uncertainty caused by intraclass heterogeneity and interclass blurring is prevalent in high-resolution r
Externí odkaz:
https://doaj.org/article/e94bceb240294f26992215fd7627384c
Publikováno v:
European Journal of Remote Sensing, Vol 56, Iss 1 (2023)
ABSTRACTThe progress in optical remote sensing technology presents both a possibility and challenge for small object segmentation task. However, the gap between human vision cognition and machine behavior still poses an inherent constrains to the int
Externí odkaz:
https://doaj.org/article/bb02d59c16a044c082a11f2edb44040a
Autor:
Jie Wang, Jindong Xu, Qianpeng Chong, Zhaowei Liu, Weiqing Yan, Haihua Xing, Qianguo Xing, Mengying Ni
Publikováno v:
Remote Sensing, Vol 15, Iss 8, p 2070 (2023)
Convolutional neural-network-based autoencoders, which can integrate the spatial correlation between pixels well, have been broadly used for hyperspectral unmixing and obtained excellent performance. Nevertheless, these methods are hindered in their
Externí odkaz:
https://doaj.org/article/d95829dddbc7405997577373adfc14dd
Publikováno v:
Applied Sciences, Vol 11, Iss 20, p 9416 (2021)
To solve the challenge of single-channel blind image separation (BIS) caused by unknown prior knowledge during the separation process, we propose a BIS method based on cascaded generative adversarial networks (GANs). To ensure that the proposed metho
Externí odkaz:
https://doaj.org/article/c45592f5bc1c44fa948c6721b0804ef4
Autor:
Mengying Ni, Chengcai Ma, Hailong Huang, Lu Han, Xiaobin Fu, Zhongli Yang, Jingwen Li, Likun Pan, Min Xu
Publikováno v:
ACS Applied Energy Materials. 5:6724-6733
Publikováno v:
IET Image Processing. 16:1897-1907
Publikováno v:
Communications in Statistics - Simulation and Computation. :1-8
In this paper, we propose an effective bootstrap algorithm to calculate the p-value of Fisher’s combination for a large number of weakly dependent p-values. The proposed bootstrap algorithm is base...