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: Applications for Future Internet; International Summit Enrique Sucar,Oscar Mayora,Enrique Munoz de Cote Conference proceedings 2017 ICST In

[复制链接]
楼主: Disperse
发表于 2025-3-25 04:43:02 | 显示全部楼层
发表于 2025-3-25 09:52:02 | 显示全部楼层
发表于 2025-3-25 12:48:18 | 显示全部楼层
发表于 2025-3-25 19:18:50 | 显示全部楼层
Fieldwork with Vulnerable Young People,tter social network is a source of valuable information in simple text and appropriated to use this technology. In this paper is described the process used to select the most suitable algorithms to analyze tweets for particular words written in Spanish, also the results obtained by every algorithm are reported.
发表于 2025-3-25 23:04:42 | 显示全部楼层
发表于 2025-3-26 00:09:04 | 显示全部楼层
Exploiting Data of the Twitter Social Network Using Sentiment Analysistter social network is a source of valuable information in simple text and appropriated to use this technology. In this paper is described the process used to select the most suitable algorithms to analyze tweets for particular words written in Spanish, also the results obtained by every algorithm are reported.
发表于 2025-3-26 04:25:53 | 显示全部楼层
发表于 2025-3-26 08:39:08 | 显示全部楼层
Towards a Generic Ontology for Video Surveillancet complex behaviors (fights, thefts, attacks). To solve these challenges, the use of ontologies has been proposed as a tool to reduce this gap between low and high level information. In this work, we present the foundations of an ontology to be used in an intelligent video surveillance system.
发表于 2025-3-26 15:00:13 | 显示全部楼层
发表于 2025-3-26 16:58:18 | 显示全部楼层
Using Intermediate Models and Knowledge Learning to Improve Stress Predictionl-world setting, from 29 employees in two different organisations over 5 weeks. To improve classification performance we propose to use .. These intermediate models represent the mood state of a person which is used to build the final stress prediction model. In particular, we obtained an accuracy of 78.2 % to classify stress levels.
 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, 2025-5-18 12:50
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