Titlebook: Roadside Video Data Analysis; Deep Learning Brijesh Verma,Ligang Zhang,David Stockwell Book 2017 Springer Nature Singapore Pte Ltd. 2017 Fe

只看該作者 · 發(fā)表于 2025-3-25 08:38:31

Studies in Computational Intelligencehttp://image.papertrans.cn/r/image/830946.jpg

只看該作者 · 發(fā)表于 2025-3-25 12:16:30

https://doi.org/10.1007/978-981-10-4539-4Feature extraction; Classified roadside objects; Roadside Fire Risk Assessment; Neural Network Learning

只看該作者 · 發(fā)表于 2025-3-25 19:49:29

只看該作者 · 發(fā)表于 2025-3-25 23:02:34

只看該作者 · 發(fā)表于 2025-3-26 00:52:15

Deep Learning Techniques for Roadside Video Data Analysis,In this chapter, we describe deep learning techniques that are proposed for roadside video data analysis. We firstly present an introduction to deep learning concepts, and a short review of several typical types of CNN.

只看該作者 · 發(fā)表于 2025-3-26 06:17:21

只看該作者 · 發(fā)表于 2025-3-26 11:02:43

只看該作者 · 發(fā)表于 2025-3-26 13:34:03

Brijesh Verma,Ligang Zhang,David StockwellHighlights deep learning, to better understand roadside video data segmentation.Provides learning techniques based on concepts for roadside video data processing.Discusses fire risk assessment based o

只看該作者 · 發(fā)表于 2025-3-26 17:53:51

		自動登錄	找回密碼
密碼			To register

關(guān)于派博傳思			派博傳思旗下網(wǎng)站			友情鏈接
派博傳思介紹	公司地理位置	論文服務(wù)流程	影響因子官網(wǎng)	吾愛論文網(wǎng)	大講堂	北京大學(xué)	Oxford Uni.	Harvard Uni.
發(fā)展歷史沿革	期刊點(diǎn)評	投稿經(jīng)驗(yàn)總結(jié)	SCIENCEGARD	IMPACTFACTOR	派博系數(shù)	清華大學(xué)	Yale Uni.	Stanford Uni.
\|Archiver\|手機(jī)版\|小黑屋\| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2026-1-24 11:49
Copyright © 2001-2015 派博傳思京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved