找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

Titlebook: Intelligent Interpretation for Geological Disasters; From Space-Air-Groun Weitao Chen,Cheng Zhong,Lizhe Wang Book 2023 The Editor(s) (if ap

[復(fù)制鏈接]
樓主: 冠軍
11#
發(fā)表于 2025-3-23 13:00:27 | 只看該作者
12#
發(fā)表于 2025-3-23 16:16:59 | 只看該作者
Geological Disaster: An Overview,nsights from recent researches, as well as gaps and challenges in current research and management efforts are also discussed. The futural directions and opportunities presented in this chapter can help to inform stakeholders and researchers on the potential approaches for managing and mitigating the impact of geological disasters.
13#
發(fā)表于 2025-3-23 21:58:27 | 只看該作者
14#
發(fā)表于 2025-3-23 23:26:49 | 只看該作者
Deep Learning Based Remote Sensing Monitoring of Landslide, sensing images is used for this study. The results indicate the framework can successfully identify most landslides in the dataset. And Faster R-CNN equipped with GCN shows a better performance than the original framework.
15#
發(fā)表于 2025-3-24 02:46:02 | 只看該作者
16#
發(fā)表于 2025-3-24 08:36:51 | 只看該作者
Book 2023t researches on high-precision recognition, monitoring, analysis, and assessment of geological disasters by using different technologies of "ground, airspace, and space-based systems" and different scales of "target-semantic-region". The main contents include:..1) Intelligent interpretation theory a
17#
發(fā)表于 2025-3-24 12:48:57 | 只看該作者
e, and space-based systems and uses deep learning technology.This book comprehensively utilizes the new generation of artificial intelligence and remote sensing science and technology to systematically carry out researches on high-precision recognition, monitoring, analysis, and assessment of geolog
18#
發(fā)表于 2025-3-24 16:22:36 | 只看該作者
Deep Learning for Long-Term Landslide Change Detection from Optical Remote Sensing Data,chnology and landslide remote sensing identification method, and also help to promote the extensive development of historical landslide cataloging and long-term landslide activity analysis, which will better support the major engineering construction and mountainous land development and management.
19#
發(fā)表于 2025-3-24 19:53:23 | 只看該作者
20#
發(fā)表于 2025-3-25 02:45:54 | 只看該作者
Weitao Chen,Cheng Zhong,Lizhe WangCombines both remote sensing and artificial intelligent from an interdisciplinary standpoint.Collects multi-source data from ground, airspace, and space-based systems and uses deep learning technology
 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 期刊點評 投稿經(jīng)驗總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機(jī)版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2026-1-18 23:01
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
道孚县| 葫芦岛市| 苍溪县| 大邑县| 乌鲁木齐县| 平原县| 无锡市| 安多县| 察哈| 敦煌市| 海兴县| 偏关县| 尚义县| 孟连| 博客| 子洲县| 荣昌县| 日照市| 朝阳市| 元江| 南城县| 平乡县| 温宿县| 仁寿县| 河东区| 阳春市| 清徐县| 岗巴县| 泉州市| 英吉沙县| 三原县| 苍南县| 宁南县| 枝江市| 陕西省| 河津市| 衡山县| 南华县| 长白| 巩留县| 宁都县|