设为首页收藏本站
开启辅助访问 切换到窄版

 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

  • ALL
  • Journals
  • Books

派博传思国际中心 »期刊书目

› BOOKS
› BOOKS with Alphabet   M (Ma,Mb,Mc, Md,Me…)

123456下一页
返回列表

Titlebook: Machine Learning for Indoor Localization and Navigation; Saideep Tiku,Sudeep Pasricha Book 2023 The Editor(s) (if applicable) and The Auth

[复制链接]
查看: 25407|回复: 57
发表于 2025-3-21 18:07:05 | 显示全部楼层 |阅读模式
书目名称Machine Learning for Indoor Localization and Navigation
编辑Saideep Tiku,Sudeep Pasricha
视频videohttp://file.papertrans.cn/621/620623/620623.mp4
概述Provides comprehensive coverage of the application of machine learning.Presents techniques to adapt and optimize machine learning models for fast, energy-efficient indoor localization.Covers design an
图书封面Titlebook: Machine Learning for Indoor Localization and Navigation; Saideep Tiku,Sudeep Pasricha Book 2023 The Editor(s) (if applicable) and The Auth
描述While GPS is the de-facto solution for outdoor positioning with a clear sky view, there is no prevailing technology for GPS-deprived areas, including dense city centers, urban canyons, buildings and other covered structures, and subterranean facilities such as underground mines, where GPS signals are severely attenuated or totally blocked. As an alternative to GPS for the outdoors, indoor localization using machine learning is an emerging embedded and Internet of Things (IoT) application domain that is poised to reinvent the way we navigate in various indoor environments. This book discusses advances in the applications of machine learning that enable the localization and navigation of humans, robots, and vehicles in GPS-deficient environments. The book explores key challenges in the domain, such as mobile device resource limitations, device heterogeneity, environmental uncertainties, wireless signal variations, and security vulnerabilities. Countering these challenges can improve theaccuracy, reliability, predictability, and energy-efficiency of indoor localization and navigation. The book identifies severalnovel energy-efficient, real-time, and robust indoor localization techniqu
出版日期Book 2023
关键词Machine learning-based indoor localization; deep learning indoor localization; indoor positioning; indo
版次1
doihttps://doi.org/10.1007/978-3-031-26712-3
isbn_softcover978-3-031-26714-7
isbn_ebook978-3-031-26712-3
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

书目名称Machine Learning for Indoor Localization and Navigation影响因子(影响力)




书目名称Machine Learning for Indoor Localization and Navigation影响因子(影响力)学科排名




书目名称Machine Learning for Indoor Localization and Navigation网络公开度




书目名称Machine Learning for Indoor Localization and Navigation网络公开度学科排名




书目名称Machine Learning for Indoor Localization and Navigation被引频次




书目名称Machine Learning for Indoor Localization and Navigation被引频次学科排名




书目名称Machine Learning for Indoor Localization and Navigation年度引用




书目名称Machine Learning for Indoor Localization and Navigation年度引用学科排名




书目名称Machine Learning for Indoor Localization and Navigation读者反馈




书目名称Machine Learning for Indoor Localization and Navigation读者反馈学科排名




单选投票, 共有 0 人参与投票
1.jpg
 

0票 0%

Perfect with Aesthetics
2.jpg
 

0票 0%

Better Implies Difficulty
3.jpg
 

0票 0%

Good and Satisfactory
4.jpg
 

0票 0%

Adverse Performance
5.jpg
 

0票 0%

Disdainful Garbage
您所在的用户组没有投票权限
富裕
回复

举报

发表于 2025-3-21 23:54:38 | 显示全部楼层
Smart Device-Based PDR Methods for Indoor Localizationon capability. Sensors embedded in these devices are relatively low-cost and convenient to carry. Consequently, leveraging the sensors embedded in smart devices has provided new opportunities for indoor PDR developments. In this chapter, we first introduce various types of smart devices and device-b
反话
回复

举报

发表于 2025-3-22 04:28:44 | 显示全部楼层
Geometric Indoor Radiolocation: History, Trends and Open Issuesrties of the received signal, the so-called geometric radiolocation techniques. A brief reference to the localization history, actors, and architectures, along of a taxonomy of the different concepts of localization, introduces the chapter, before presenting a detailed discussion of the most common
Conspiracy
回复

举报

发表于 2025-3-22 07:57:42 | 显示全部楼层
Indoor Localization Using Trilateration and Location Fingerprinting Methodsl techniques to identify the location of the intersection point of three circles. A location “fingerprinting” algorithm is normally comprised of two stages. In the first stage, a positioning fingerprint database is established and the second stage is matching the fingerprint with the database. Kalma
Ptosis
回复

举报

发表于 2025-3-22 10:51:54 | 显示全部楼层
overrule
回复

举报

发表于 2025-3-22 16:19:23 | 显示全部楼层
Allergic
回复

举报

发表于 2025-3-22 19:48:13 | 显示全部楼层
A Scalable Framework for Indoor Localization Using Convolutional Neural Networkstals, and underground mines. Most prior works in the domain of indoor localization deliver inadequate localization accuracies without expensive infrastructure. Alternatively, methodologies employing inexpensive off-the-shelf devices that are ubiquitous in nature lack consistency in localization qual
闲逛
回复

举报

发表于 2025-3-22 21:13:11 | 显示全部楼层
laceration
回复

举报

发表于 2025-3-23 03:47:46 | 显示全部楼层
Exploiting Fingerprint Correlation for Fingerprint-Based Indoor Localization: A Deep Learning-Based lying various fingerprints in improving localization accuracy still remains unknown. Moreover, how to design efficient indoor localization methods through fully exploiting the features of different fingerprints is to be explored as well. In this chapter, we investigate the location error of a finger
多山
回复

举报

发表于 2025-3-23 06:25:32 | 显示全部楼层
genesis
回复

举报

下一页 »
123456下一页
返回列表
 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, 2025-8-28 13:44
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