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: Geometry and Vision; First International Minh Nguyen,Wei Qi Yan,Harvey Ho Conference proceedings 2021 Springer Nature Switzerland AG 2021

[复制链接]
楼主: 黑暗社会
发表于 2025-3-28 15:43:11 | 显示全部楼层
Traffic-Sign Recognition Using Deep Learning,r the traffic-sign recognition in New Zealand. In order to determine which deep learning models are the most suitable one for the TSR, we choose two kinds of models to conduct deep learning computations: Faster R-CNN and YOLOv5. According to the scores of various metrics, we summarized the pros and cons of the picked models for the TSR task.
发表于 2025-3-28 18:45:28 | 显示全部楼层
Segment- and Arc-Based Vectorizations by Multi-scale/Irregular Tangential Covering,construct the input noisy objects into cyclic contours made of lines or arcs with a minimal number of primitives. We explain our novel complete pipeline in this work, and present its experimental evaluation by considering both synthetic and real image data.
发表于 2025-3-29 01:39:26 | 显示全部楼层
发表于 2025-3-29 06:40:49 | 显示全部楼层
发表于 2025-3-29 07:41:40 | 显示全部楼层
发表于 2025-3-29 13:29:50 | 显示全部楼层
发表于 2025-3-29 17:24:11 | 显示全部楼层
发表于 2025-3-29 21:09:17 | 显示全部楼层
Apple Ripeness Identification Using Deep Learning,ifiers are able to achieve the best result, i.e., the ripeness class of an apple from a given digital image is able to be precisely predicted. We have optimized the deep learning models and trained the classifiers so as to achieve the best outcome.
发表于 2025-3-30 00:18:45 | 显示全部楼层
发表于 2025-3-30 04:13:44 | 显示全部楼层
Towards a Generic Bicubic Hermite Mesh Template for Cow Udders,ed correspondences occur due to data point occlusion and insufficient sampling points. In summary, a first parametric mesh based 3D model has been constructed for the cow udder and teat. We have examined the efficacy of the morphing algorithm, and also the issues to be solved for a statistical cow udder and teat model.
 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 SITEMAP 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.
|Archiver|手机版|小黑屋| 派博传思国际 ( 京公网安备110108008328) GMT+8, 2025-5-21 21:39
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