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检索条件"主题词=Object-Based Image Analysis"
495 条 记 录,以下是121-130 订阅
排序:
AN IMPROVED object CNN METHOD FOR CLASSIFICATION OF HIGH-RESOLUTION REMOTE SENSING imageRY
AN IMPROVED OBJECT CNN METHOD FOR CLASSIFICATION OF HIGH-RES...
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IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
作者: Li, Zhiqing Li, Erzhu Su, Zhigang Xu, Tianyu Jiangsu Normal Univ Sch Geog Geomat & Planning Xuzhou 221116 Jiangsu Peoples R China Zhengyuan Geomat Grp Co Ltd Shandong Branch Jinan 250101 Shandong Peoples R China
Land cover and land use (LULC) classification of very fine spatial resolution remote sensing images is a challenging task. Though the object-based convolutional neural network (OCNN) has proven to be an effective meth... 详细信息
来源: 评论
Combining OBIA approach and Machine Learning algorithm to extract photovoltaic panels from Sentinel-2 images automatically  24
Combining OBIA approach and Machine Learning algorithm to ex...
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Conference on Remote Sensing for Agriculture, Ecosystems, and Hydrology XXIV Part of SPIE Remote Sensing Conferene
作者: Ladisa, Claudio Capolupo, Alessandra Ripa, Maria Nicolina Tarantino, Eufemia Politecn Bari Dept Civil Environm Land Construct & Chem DICATEC Via Orabona 4 I-70125 Bari Italy Univ Tuscia Dept Agr & Forest Sci DAFNE Via S Camillo de Lellis Snc I-01100 Viterbo Italy
The Energy Union Framework Strategy is pushing the entire world to move from fossil fuels to renewable energy to tackle climate changes and mitigate their effects. Among the clean energy alternatives, the sun is recog... 详细信息
来源: 评论
Machine learning and multi-sensor data fusion for mapping lithology: A case study of Kowli-kosh area, SW Iran
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ADVANCES IN SPACE RESEARCH 2021年 第10期68卷 3992-4015页
作者: Shayeganpour, Samira Tangestani, Majid H. Gorsevski, Pece V. Shiraz Univ Fac Sci Dept Earth Sci Shiraz Iran Bowling Green State Univ Dept Geog Bowling Green OH 43403 USA
Lithological maps derived from traditional pixel-based image analysis are widely established in remote sensing. Recent development of new segmentation-based approaches such as object-based image analysis (OBIA) has le... 详细信息
来源: 评论
Quantifying the Long-Term Expansion and Dieback of Spartina Alterniflora Using Google Earth Engine and object-based Hierarchical Random Forest Classification
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IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 2021年 14卷 9781-9793页
作者: Yan, Dandan Li, Jingtai Yao, Xiuying Luan, Zhaoqing Nanjing Forestry Univ Coll Biol & Environm Coinnovat Ctr Sustainable Forestry Southern China Nanjing 210037 Peoples R China
The overwhelming spread of Spartina alterniflora (S. alterniflora) (smooth cordgrass) over recent decades has put many native plant communities and coastal environments at risk. Therefore, long-term monitoring of S. a... 详细信息
来源: 评论
Improving hyperspectral image segmentation by applying inverse noise weighting and outlier removal for optimal scale selection
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ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING 2021年 171卷 348-366页
作者: Dao, Phuong D. Mantripragada, Kiran He, Yuhong Qureshi, Faisal Z. Univ Toronto Dept Geog Geomat & Environm 3359 Mississauga Rd Mississauga ON L5L 1C6 Canada Univ Toronto Sch Environm 33 Willcocks St Toronto ON M5S 3E8 Canada Ontario Tech Univ Fac Sci 2000 Simcoe St North Oshawa ON L1G OC5 Canada
Optimal scale selection for image segmentation is an essential component of the object-based image analysis (OBIA) and interpretation. An optimal segmentation scale is a scale at which image objects, overall, best rep... 详细信息
来源: 评论
Discrepancy measures for selecting optimal combination of parameter values in object-based image analysis
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ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING 2012年 第1期68卷 144-156页
作者: Liu, Yong Bian, Ling Meng, Yuhong Wang, Huanping Zhang, Shifu Yang, Yining Shao, Xiaomin Wang, Bo Lanzhou Univ Coll Earth & Environm Sci Lanzhou 730000 Peoples R China SUNY Buffalo Dept Geog Amherst NY 14261 USA
Most object-based image analysis use parameters to control the size, shape, and homogeneity of segments. Because each parameter may take a range of possible values, different combinations of value between parameters m... 详细信息
来源: 评论
Discriminating crops/weeds in an upland rice field from UAV images with the SLIC-RF algorithm
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PLANT PRODUCTION SCIENCE 2021年 第2期24卷 198-215页
作者: Kawamura, Kensuke Asai, Hidetoshi Yasuda, Taisuke Soisouvanh, Pheunphit Phongchanmixay, Sengthong Japan Int Res Ctr Agr Sci JIRCAS Tsukuba Ibaraki Japan Yamanashi Prefectural Govt Mt Fuji Res Inst Fujiyoshida Yamanashi Japan Natl Agr & Forestry Res Inst NAFRI Rice Res Ctr Viangchan Laos
In this study, we propose a method for discriminating crops/weeds in upland rice fields using a commercial unmanned aerial vehicles (UAVs) and red-green-blue (RGB) cameras with the simple linear iterative clustering (... 详细信息
来源: 评论
object-based crop classification in Hetao plain using random forest
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EARTH SCIENCE INFORMATICS 2021年 第1期14卷 119-131页
作者: Su, Tengfei Zhang, Shengwei Inner Mongolia Agr Univ Coll Water Conservancy & Civil Engn 306 Zhaowuda Rd Hohhot Peoples R China Inner Mongolia Autonomous Reg Key Lab Big Data Re 306 Zhaowuda Rd Hohhot Peoples R China
Crop classification based on object-based image analysis (OBIA) is increasingly reported. However, it is still challenging to produce high-quality crop type maps by using recent techniques. This article introduces a n... 详细信息
来源: 评论
Detection of Oil Pollution Using SAR and Optical Remote Sensing imagery: A Case Study of the Persian Gulf
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JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING 2021年 第10期49卷 2377-2385页
作者: Mohammadi, Mina Sharifi, Alireza Hosseingholizadeh, Mohammad Tariq, Aqil Shahid Rajaee Teacher Training Univ Fac Civil Engn Dept Surveying Engn Tehran Iran Wuhan Univ State Key Lab Informat Engn Surveying Mapping & R Wuhan 430079 Peoples R China
The coastal regions in the Persian Gulf are renowned for having the largest oil reserves. Pipelines, as a means of oil transportation, are one of the most common options for transporting petroleum products in these re... 详细信息
来源: 评论
A Combination of OBIA and Random Forest based on Visible UAV Remote Sensing for Accurately Extracted Information about Weeds in Areas with Different Weed Densities in Farmland
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REMOTE SENSING 2023年 第19期15卷 4696页
作者: Feng, Chao Zhang, Wenjiang Deng, Hui Dong, Lei Zhang, Houxi Tang, Ling Zheng, Yu Zhao, Zihan Chengdu Univ Technol Coll Earth Sci Chengdu 610059 Peoples R China Tibet Autonomous Reg Geol Min Explorat & Dev Bur 2 Geol Team Lhasa 850007 Peoples R China Fujian Agr & Forestry Univ Coll Forestry Fuzhou 350002 Peoples R China
Weeds have a significant impact on the growth of rice. Accurate information about weed infestations can provide farmers with important information to facilitate the precise use of chemicals. In this study, we utilized... 详细信息
来源: 评论