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: Machine Learning Paradigms; Applications of Lear George A. Tsihrintzis,Maria Virvou,Lakhmi C. Jain Book 2019 Springer Nature Switzerland AG

[复制链接]
楼主: 母牛胆小鬼
发表于 2025-3-28 15:17:16 | 显示全部楼层
Machine Learning Approaches for Pap-Smear Diagnosis: An Overviewl data analysis problems, such as optimizing the Pap-Smear or Pap-Test diagnosis. Pap-Smear or Pap-Test is a method for diagnosing Cervical Cancer (4th leading cause of female cancer and 2nd common female cancer in the women aged 14–44 years old), invented by Dr. George Papanicolaou in 1928 (Bruni e
发表于 2025-3-28 19:00:08 | 显示全部楼层
Multi-kernel Analysis Paradigm Implementing the Learning from Loads Approach for Smart Power Systemsa new machine learning paradigm is presented focusing on the analysis of recorded electricity load data. The presented paradigm utilizes a set of multiple kernel functions to analyze a load signal into a set of components. Each component models a set of different data properties, while the coefficie
发表于 2025-3-28 23:48:43 | 显示全部楼层
Conceptualizing and Measuring Energy Security: Geopolitical Dimensions, Data Availability, Quantitat to energy security research that aims to estimate a quantitative energy security index with a geopolitical focus, by providing an in-depth dynamic geopolitical look into the history, evolution, dimensions, data, estimation, taxonomy, and forecasts of energy security. Discussion is complemented with
发表于 2025-3-29 06:19:03 | 显示全部楼层
Automated Stock Price Motion Prediction Using Technical Analysis Datasets and Machine Learning in which the process of forecasting is based on Machine Learning. The system has been developed following the cloud computing paradigm consisting of a backend application in Google’s API Hosting Cloud and using an Android front end using inspiring, contemporary styles of tools and libraries and har
发表于 2025-3-29 09:41:43 | 显示全部楼层
发表于 2025-3-29 12:12:05 | 显示全部楼层
发表于 2025-3-29 16:38:39 | 显示全部楼层
发表于 2025-3-29 21:16:11 | 显示全部楼层
Analytics and Evolving Landscape of Machine Learning for Emergency Responseision makers. This has resulted in new challenges related to the effective management of large volumes of data. In this regard, the role of machine learning in mass emergency and humanitarian crises is constantly evolving and gaining traction. As a branch of artificial intelligence, machine learning
 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 23:47
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