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: Data Science; 10th International C Chengzhong Xu,Haiwei Pan,Zeguang Lu Conference proceedings 2024 The Editor(s) (if applicable) and The Au

[复制链接]
楼主: Gram114
发表于 2025-3-30 09:37:16 | 显示全部楼层
https://doi.org/10.1007/978-3-531-94182-0and stable operation. Traditional computer vision detection model have problems such as low detection efficiency, many missed detections and poor robustness. To address these problems, we propose a single-stage target detection model PDTNet, which can better extract defect features and can be better
发表于 2025-3-30 16:25:48 | 显示全部楼层
发表于 2025-3-30 17:57:05 | 显示全部楼层
发表于 2025-3-30 22:14:55 | 显示全部楼层
978-981-97-8748-7The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
发表于 2025-3-31 01:47:52 | 显示全部楼层
Android Malware Detection Method Based on Machine Learning 80%, whereas the dynamic method achieves an accuracy of 91%. Through the utilization of software intention analysis and permission usage checks in combination, the accuracy rate can be further enhanced to 94%. Upon comparison of the different algorithms utilized in each detection method, it is conc
发表于 2025-3-31 05:46:30 | 显示全部楼层
发表于 2025-3-31 10:23:49 | 显示全部楼层
Personalized Novel Recommendation System Based on Filtering and Sentiment Analysisommendation system that incorporates sentiment analysis together with content-based recommendation and coordinated filtering. Tests were carried out on publicly available datasets and shown superior accuracy in comparison to cutting-edge techniques.
发表于 2025-3-31 13:55:25 | 显示全部楼层
发表于 2025-3-31 19:17:07 | 显示全部楼层
IPFS-DKRM: An Efficient Keyword Retrieval Model of IPFS Based on ART efficient retrieval services. In the simulation experiment, the index of open source data set Crosswikis was constructed, and the performance was analyzed based on the results of Siva data. The experimental results showed that compared with the Siva model, the response retrieval time of IPFS-DKRM w
 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, 2025-5-17 23:57
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