Fuzzy Machine Learning Algorithms for Remote Sensing Image Classification
暫譯: 模糊機器學習演算法在遙感影像分類中的應用

Kumar, Anil, Upadhyay, Priyadarshi, Kumar, A. Senthil

Fuzzy Machine Learning Algorithms for Remote Sensing Image Classification
  • 出版商: CRC
  • 出版日期: 2020-07-20
  • 售價: $4,270
  • 貴賓價: 9.5 折 $4,057
  • 語言: 英文
  • 頁數: 208
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 036735571X
  • ISBN-13: 9780367355715
  • 相關分類: Machine Learning、Algorithms-data-structures

    • 海外代購書籍(需單獨結帳)

商品描述

This book covers the state of art image classification methods for discrimination of earth objects from remote sensing satellite data with an emphasis on fuzzy based learning methods including applications for preparing land cover classification outputs from actual satellite data. It provides details about the temporal indices database using proposed class-based sensor independent approach supported by practical examples. Fuzzy based algorithms with machine learning algorithms to prepare land cover maps is discussed. Accuracy assessment for soft classification outputs are included and all algorithms are supported by in-house developed tool as Sub-pixel Multi-spectral Image Classifier. Aimed at researchers, graduate students, professionals in earth remote sensing, remote sensing image and data processing, geography and geoinformation science, image classification, this book Exclusively focuses on using fuzzy classification to remote sensing images Covers Sub Pixel Multi-Spectral Image Classifier Tool (SMIC) to support discussed algorithms Explains fuzzy and learning based classifiers with in-house developed SMIC tool Discusses how ANN, CNN, RNN and hybrid learning classifiers application on remote sensing images Combines explanation of the algorithms with examples, graph, and charts.

商品描述(中文翻譯)

本書涵蓋了最先進的影像分類方法，旨在從遙感衛星數據中區分地球物體，特別強調基於模糊學習的方法，包括從實際衛星數據準備土地覆蓋分類輸出的應用。它提供了有關時間指數數據庫的詳細資訊，使用所提出的基於類別的無感測器獨立方法，並輔以實際範例。書中討論了使用機器學習算法的模糊算法來準備土地覆蓋圖。還包括對軟分類輸出的準確性評估，所有算法均由內部開發的工具——子像素多光譜影像分類器（Sub-pixel Multi-spectral Image Classifier）支持。本書針對地球遙感、遙感影像與數據處理、地理學及地理資訊科學、影像分類等領域的研究人員、研究生及專業人士，專注於使用模糊分類技術處理遙感影像。涵蓋了支持所討論算法的子像素多光譜影像分類器工具（SMIC），解釋了基於模糊和學習的分類器及內部開發的SMIC工具，討論了人工神經網絡（ANN）、卷積神經網絡（CNN）、遞歸神經網絡（RNN）及混合學習分類器在遙感影像上的應用，並結合算法的解釋與範例、圖表和圖形。

作者簡介

Anil Kumar is working as Scientist/Engineer-'SG' & Head Photogrammetry and Remote Sensing Department at Indian Institute of Remote Sensing (IIRS), Indian Space Research organisation (ISRO), Dehradun, India. He received his B.Tech degree in Civil Engineering from University of Lucknow, India and M.E. degre as well as inservise Ph.D in soft computing from Indian Institute of Technology, Roorkee, India. He has published 46 papers in journals. Guided 36 masters and 5 Ph.D thesis. He has been recipient of the prestigious P. R. Pisharoty Memorial Award conferred by the Indian Society of Remote Sensing. He is a life member of the Indian Society of Remote Sensing. His current research interests are in Soft computing, Deep Learning, Multi-sensor temporal data processing, Digital Photogrammetry, GPS and LiDAR.

Priyadarshi Upadhyay is working as a Scientist/Engineer-SD in Uttarakhand Space Application Centre (USAC), Dehradun, India. He received his M.Sc. degree in Physics from Kumaun University Nainital, India and M.Tech. degree in Remote Sensing from Birla Institute of Technology, Mesra Ranchi, India. He has received his Ph.D. degree from Indian Institute of Technology Roorkee, India in the area of time series remote sensing for single crop identification. He has published 15 research papers in various International Journals, Internation and National Conferences. He has been awarded by presitigious CSIR-NET, GATE and MHRD Travel Grant Fellowships. He is a life member of Indian Society of Remote Sensing and The Institute of Engineers (India). His current research interest are Microwave Remote Sensing for Soil Moisture and Crop Mapping, Polarimatric and Inerferrometric SAR, Hyperspectral and Optical Remote Sensing, Climate Change, Ecological Studies in Himalayan Region for Economically Important Crops and Plants.

A. Senthil Kumar is the Director of UN-affliated Centre for Space Science and Technology Education in Asia and the Pacific in Dehradun, India. He received M.Sc. (Engg.) and Ph.D. from the Indian Institute of Science, Bangalore in the field of image processing in 1985 and 1990 respectively. He joined ISRO in 1991. Since then he has served in Indian Remote Sensing programs in various capacities. He has published more than 120 technical papers in international journals and conferences and co-edited a book on Remote Sensing of Northwest Himalayan Ecosystems. He has received ISRO Team awards for his contributions to Chandrayaan-1 and Cartosat-1 missions. His research areas include remote sensing sensor characterization, radiometric data processing, image restoration, data fusion techniques and in soft computing techniques. He has also been a recipient of the prestigious Prof. Satish Dhawan Award conferred by the Indian Society of Remote Sensing. He is a life member of the Indian Society of Remote Sensing and the Indian Society of Geomatics.

作者簡介(中文翻譯)

Anil Kumar 目前擔任印度空間研究組織（ISRO）德拉敦印度遙感研究所（IIRS）科學家/工程師-‘SG’及攝影測量與遙感部門負責人。他在印度盧克瑙大學獲得土木工程的B.Tech學位，並在印度羅爾基的印度理工學院獲得軟計算的碩士學位及在職博士學位。他已在期刊上發表了46篇論文，指導了36篇碩士論文和5篇博士論文。他曾獲得印度遙感學會頒發的著名P. R. Pisharoty紀念獎。他是印度遙感學會的終身會員。他目前的研究興趣包括軟計算、深度學習、多感測器時間數據處理、數位攝影測量、GPS和LiDAR。

Priyadarshi Upadhyay 目前在印度德拉敦的烏塔拉坎德空間應用中心（USAC）擔任科學家/工程師-SD。他在印度奈尼塔爾的庫瑪雲大學獲得物理學碩士學位，並在印度梅斯拉蘭契的比爾拉科技學院獲得遙感的M.Tech學位。他在印度羅爾基的印度理工學院獲得博士學位，研究主題為單一作物識別的時間序列遙感。他在各種國際期刊和國際及國內會議上發表了15篇研究論文，並獲得了著名的CSIR-NET、GATE和MHRD旅行獎學金。他是印度遙感學會和印度工程師學會的終身會員。他目前的研究興趣包括土壤濕度和作物繪圖的微波遙感、極化和干涉合成孔徑雷達（SAR）、高光譜和光學遙感、氣候變遷、以及對喜馬拉雅地區經濟重要作物和植物的生態研究。

A. Senthil Kumar 是聯合國附屬的亞洲及太平洋地區空間科學與技術教育中心的主任，位於印度德拉敦。他於1985年和1990年在班加羅爾的印度科學研究院獲得工程碩士（M.Sc. (Engg.)）和博士學位，專攻影像處理。他於1991年加入ISRO，並自此在印度遙感計畫中擔任多個職位。他在國際期刊和會議上發表了超過120篇技術論文，並共同編輯了一本關於西北喜馬拉雅生態系統遙感的書籍。他因對Chandrayaan-1和Cartosat-1任務的貢獻而獲得ISRO團隊獎。他的研究領域包括遙感傳感器特性、輻射數據處理、影像修復、數據融合技術及軟計算技術。他也曾獲得印度遙感學會頒發的著名Prof. Satish Dhawan獎。他是印度遙感學會和印度地理信息學會的終身會員。

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