找回密码
 To register

QQ登录

只需一步,快速开始

扫一扫,访问微社区

Titlebook: Communications, Signal Processing, and Systems; Proceedings of the 2 Qilian Liang,Xin Liu,Baoju Zhang Conference proceedings 2020 Springer

[复制链接]
楼主: 变更
发表于 2025-3-25 06:45:17 | 显示全部楼层
https://doi.org/10.1007/978-94-017-3023-5investigate how the number of generated samples influences the re-ID performance. We do several experiments on the Market1501 database, and the experimental results are of essential reference value to this research field.
发表于 2025-3-25 09:49:43 | 显示全部楼层
发表于 2025-3-25 15:43:15 | 显示全部楼层
发表于 2025-3-25 17:55:18 | 显示全部楼层
发表于 2025-3-25 21:02:45 | 显示全部楼层
Solar Photovoltaic Power Plantsive fields and scales, which are expected to obtain more texture details. Meanwhile, the local and global residual learning strategies are employed to prevent overfitting and to improve reconstruction quality. Compared with the classic convolutional neural network-based algorithms, the proposed method achieves better numerical and visual effects.
发表于 2025-3-26 03:32:05 | 显示全部楼层
Scattering Polarization in the Chromosphere,s of Harris corner detection algorithm in image scaling, rotation or gray scale change, improves its disadvantage of scaleinvariance, and has strong anti-noise and real-time performance. It has good anti-noise and real-time performance.
发表于 2025-3-26 07:19:38 | 显示全部楼层
Stokes Profiles Inversion Techniques,ic concepts and algorithm processes are introduced. Furthermore, the paper discusses the advantages and disadvantages of different algorithms, which will offer potential research direction for the future development of SR.
发表于 2025-3-26 11:07:29 | 显示全部楼层
发表于 2025-3-26 14:37:44 | 显示全部楼层
发表于 2025-3-26 17:03:56 | 显示全部楼层
Image-Based Detecting the Level of Water Using Dictionary Learningon can be transformed to the problem of classifying each image into two classes of ruler and water. As dictionary learning model has shown, its ability and efficiency in image classification problems, it is utilized in this paper to solve the problem of water level detection.
 关于派博传思  派博传思旗下网站  友情链接
派博传思介绍 公司地理位置 论文服务流程 影响因子官网 吾爱论文网 大讲堂 北京大学 Oxford Uni. Harvard Uni.
发展历史沿革 期刊点评 投稿经验总结 SCIENCEGARD IMPACTFACTOR 派博系数 清华大学 Yale Uni. Stanford Uni.
QQ|Archiver|手机版|小黑屋| 派博传思国际 ( 京公网安备110108008328) GMT+8, 2025-8-25 22:13
Copyright © 2001-2015 派博传思   京公网安备110108008328 版权所有 All rights reserved
快速回复 返回顶部 返回列表