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检索条件"主题词=Object-based Classification"
321 条 记 录,以下是1-10 订阅
object-based classification of hyperspectral images based on weighted genetic algorithm and deep learning model
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APPLIED GEOMATICS 2023年 第1期15卷 227-238页
作者: Akbari, Davood Akbari, Vahid Univ Zabol Fac Engn Dept Geomat Engn Zabol Iran Univ Stirling Fac Nat Sci Dept Comp Sci & Math Stirling Scotland
Numerous uses of the hyperspectral remote sensing technology exist for identifying land cover and tracking its evolution. The classification of hyperspectral images must now take into account both spectral and spatial... 详细信息
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The potential of object-based classification for geological mapping: Applications to the volcanic region of Vakinankaratra (central Madagascar)
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JOURNAL OF AFRICAN EARTH SCIENCES 2025年 228卷
作者: Ranomenjanahary, Frederic L. Srarfi, Feyda Razafimahatratra, Dieudonne Rakotomanana, Dominique Hamdi, Mohamed S. Abidi, Riadh Randriamalala, Josoa R. Shimi, Najet Slim Univ Tunis Manar Fac Sci Tunis Dept Geol Lab 3G LR18ES37 BP 94 Tunis 1068 Tunisia Univ Antananarivo Ecole Doctorale Gest Ressources Nat & Dev ED GRND Antananarivo 101 Madagascar Univ Antananarivo Ecole Super Polytech Ment Genie Geol BP 1500 Antananarivo 102 Madagascar Univ Antananarivo Ecole Super Sci Agron Ment Foresterie & Environm BP 175 Antananarivo 101 Madagascar
A geological map is an indispensable instrument in the field of geological research. In the past, the sole method employed for the production of geological maps was manual mapping. This approach is costly in terms of ... 详细信息
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Perturbed peer model with joint confidence for semi-supervised object-based classification in urban area
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INTERNATIONAL JOURNAL OF REMOTE SENSING 2023年 第14期44卷 4417-4440页
作者: Wang, Wenye Zhang, Xueliang Xiao, Pengfeng Su, Qi Nanjing Univ Sch Geog & Ocean Sci Jiangsu Prov Key Lab Geog Informat Sci & Technol Key Lab Land Satellite Remote Sensing Applicat Min Nanjing Jiangsu Peoples R China Nanjing Univ Sch Geog & Ocean Sci Jiangsu Prov Key Lab Geog Informat Sci & Technol Key Lab Land Satellite Remote Sensing Applicat Min Nanjing 210023 Jiangsu Peoples R China
The application of deep learning (DL) improves the accuracy of object-based classification in urban area, but the huge numbers of labelled samples required for training DL models are difficult to obtain. To address th... 详细信息
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Enhanced snow cover mapping using object-based classification and normalized difference snow index (NDSI)
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EARTH SCIENCE INFORMATICS 2023年 第3期16卷 2813页
作者: Raghubanshi, Sudhanshu Agrawal, Ritesh Rathore, Bhanu Prakash Space Applicat Ctr ISRO Ahmadabad 380015 Gujarat India
The study aims to improve the classification and mapping of snow cover over the Himalayan region, which is essential for assessing water availability and understanding hydrological and climatic interactions. The norma... 详细信息
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A hybrid machine learning technique for feature optimization in object-based classification of debris-covered glaciers
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AIN SHAMS ENGINEERING JOURNAL 2022年 第6期13卷
作者: Sharda, Shikha Srivastava, Mohit Gusain, Hemendra Singh Sharma, Naveen Kumar Bhatia, Kamaljit Singh Bajaj, Mohit Kaur, Harsimrat Zawbaa, Hossam M. Kamel, Salah IK Gujral Punjab Tech Univ Dept Elect & Commun Engn Jalandhar 144603 Punjab India Chandigarh Engn Coll Dept Elect & Commun Engn Mohali 140307 Punjab India DRDO Inst Technol Management ITM Mussoorie 248179 India I K Gujral Punjab Tech Univ Dept Elect Engn Jalandhar 144603 Punjab India GB Pant Inst Engn & Technol Dept Elect & Commun Engn Pauri Garhwal 246194 India Natl Inst Technol Dept Elect & Elect Engn Delhi 110040 India CT Inst Engn & Technol Dept Elect & Commun Engn Jalandhar 144623 Punjab India Beni Suef Univ Fac Comp & Artificial Intelligence Bani Suwayf Egypt Technol Univ Dublin Dublin Ireland Aswan Univ Fac Engn Elect Engn Dept Aswan 81542 Egypt Technol Univ Dublin Cabra East Pk House191 N Circular Rd Dublin D07 EWV4 Ireland
object-based features like spectral, topographic, and textural are supportive to determine debris-covered glacier classes. The original feature space includes relevant and irrelevant features. The inclusion of all the... 详细信息
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Semi-automatic extraction of land degradation processes using multi sensor data by applying object based classification technique
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APPLIED GEOMATICS 2023年 第1期15卷 239-248页
作者: Raghubanshi, Sudhanshu Agrawal, Ritesh Rajawat, A. S. Rajak, D. Ram Space Applicat Ctr ISRO Ahmadabad 380015 India
A semi-automated method has been developed for the extraction of land degradation processes using multi sensor data by applying an object-based classification. The object-based approach creates homogenous objects, whi... 详细信息
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An Efficient Multi-stage object-based classification to Extract Urban Building Footprints from HR Satellite Images
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TRAITEMENT DU SIGNAL 2021年 第1期38卷 191-196页
作者: Pendyala, Gopala Krishna V. S. S. N. Kalluri, Hemantha Kumar Rao, Venkateswara C. Natl Remote Sensing Ctr Hyderabad 500037 Telangana India Vignans Fdn Sci Technol & Res Dept Comp Sci & Engn Vadlamudi 522213 Andhra Pradesh India
Urban building information can be effectively extracted by applying object-based image segmentation and multi-stage thresholding on High Resolution (HR) remote sensing satellite imageries. This study provides the resu... 详细信息
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object-based classification of hyperspectral data using Random Forest algorithm
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Geo-Spatial Information Science 2018年 第2期21卷 127-138页
作者: Saeid Amini Saeid Homayouni Abdolreza Safari Ali A.Darvishsefat School of Surveying and Geospatial Engineering College of EngineeringUniversity of TehranTehranIran Department of Geography Environment and GeomaticsUniversity of OttawaOttawaCanada Faculty of Natural Resources Department of ForestryUniversity of TehranKarajIran
This paper presents a new framework for object-based classification of high-resolution hyperspectral *** multi-step framework is based on multi-resolution segmentation(MRS)and Random Forest classifier(RFC)*** first st... 详细信息
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Potential of Multi-scale Completed Local Binary Pattern for object based classification of Very High Spatial Resolution Imagery
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JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING 2021年 第6期49卷 1245-1255页
作者: Chairet, Radhia Ben Salem, Yassine Aoun, Mohamed Univ Gabes Res Lab Modeling Anal & Control Syst MACS Natl Engn Sch Gabes ENIG Gabes Tunisia
This paper explores the potentiality of using the completed local binary pattern (CLBP) for the classification of an urbanized oasis area situated in southeastern Tunisia, in very high spatial resolution GeoEye imager... 详细信息
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Forest structure parameter extraction using SPOT-7 satellite data by object- and pixel-based classification methods
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ENVIRONMENTAL MONITORING AND ASSESSMENT 2020年 第1期192卷 43-43页
作者: Rahimizadeh, Naimeh Kafaky, Sasan Babaie Sahebi, Mahmod Reza Mataji, Asadollah Islamic Azad Univ Sci & Res Branch Dept Environm & Nat Resources Tehran Iran KN Toosi Univ Technol Geodesy & Geomat Engn Fac Tehran Iran
Using satellite data to extract forest structure mapping parameters assists forest management. In this research, structural parameters including species, density, canopy, and gaps were extracted from SPOT-7 satellite ... 详细信息
来源: 评论