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Refinado por: Base de dados/Biblioteca: IngentaConnect Journals remover Nome da Publicação: International Journal Of Remote Sensing remover assunto: Remote Sensing remover Neural Networks remover
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A neurocomputing model for SODAR structure classification
A neurocomputing model for SODAR structure classification
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A neurocomputing model for SODAR structure classification

Chandara Deb, Narayan ; Pal, Srimanta ; Chandra Patranabis, Dipak ; Dutta, H. N.

International journal of remote sensing, 2010-04, Vol.31 (11), p.2995-3018 [Periódico revisado por pares]

Abingdon: Taylor & Francis

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2
Comparison of modelling ANN and ELM to estimate solar radiation over Turkey using NOAA satellite data
Comparison of modelling ANN and ELM to estimate solar radiation over Turkey using NOAA satellite data
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Comparison of modelling ANN and ELM to estimate solar radiation over Turkey using NOAA satellite data

SAHIN, Mehmet

International journal of remote sensing, 2013-11, Vol.34 (21), p.7508-7533 [Periódico revisado por pares]

Abingdon: Taylor & Francis

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3
Multi-scale crown closure retrieval for moso bamboo forest using multi-source remotely sensed imagery based on geometric-optical and Erf-BP neural network models
Multi-scale crown closure retrieval for moso bamboo forest using multi-source remotely sensed imagery based on geometric-optical and Erf-BP neural network models
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Multi-scale crown closure retrieval for moso bamboo forest using multi-source remotely sensed imagery based on geometric-optical and Erf-BP neural network models

Wang, Cong ; Du, Huaqiang ; Xu, Xiaojun ; Han, Ning ; Zhou, Guomo ; Sun, Shaobo ; Gao, Guolong

International journal of remote sensing, 2015-11, Vol.36 (21), p.5384-5402 [Periódico revisado por pares]

Taylor & Francis

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4
Quantitative modelling for leaf nitrogen content of winter wheat using UAV-based hyperspectral data
Quantitative modelling for leaf nitrogen content of winter wheat using UAV-based hyperspectral data
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Quantitative modelling for leaf nitrogen content of winter wheat using UAV-based hyperspectral data

Liu, Haiying ; Zhu, Hongchun ; Wang, Ping

International journal of remote sensing, 2017-05, Vol.38 (8-10), p.2117-2134 [Periódico revisado por pares]

London: Taylor & Francis

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5
Very high-resolution mapping of emerging biogenic reefs using airborne optical imagery and neural network: the honeycomb worm (Sabellaria alveolata) case study
Very high-resolution mapping of emerging biogenic reefs using airborne optical imagery and neural network: the honeycomb worm (Sabellaria alveolata) case study
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Very high-resolution mapping of emerging biogenic reefs using airborne optical imagery and neural network: the honeycomb worm (Sabellaria alveolata) case study

Collin, Antoine ; Dubois, Stanislas ; Ramambason, Camille ; Etienne, Samuel

International journal of remote sensing, 2018-09, Vol.39 (17), p.5660-5675 [Periódico revisado por pares]

London: Taylor & Francis

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6
Segmentation-based classification for 3D point clouds in the road environment
Segmentation-based classification for 3D point clouds in the road environment
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Segmentation-based classification for 3D point clouds in the road environment

Xiang, Binbin ; Yao, Jian ; Lu, Xiaohu ; Li, Li ; Xie, Renping ; Li, Jie

International journal of remote sensing, 2018-10, Vol.39 (19), p.6182-6212 [Periódico revisado por pares]

London: Taylor & Francis

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7
A novel vehicle tracking and speed estimation with varying UAV altitude and video resolution
A novel vehicle tracking and speed estimation with varying UAV altitude and video resolution
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A novel vehicle tracking and speed estimation with varying UAV altitude and video resolution

Chen, Yuqing ; Zhao, Dongyang ; Er, Meng Joo ; Zhuang, Yan ; Hu, Huosheng

International journal of remote sensing, 2021-06, Vol.42 (12), p.4437-4462 [Periódico revisado por pares]

London: Taylor & Francis

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8
Remotely Piloted Aircraft Systems (RPAS) and machine learning: A review in the context of forest science
Remotely Piloted Aircraft Systems (RPAS) and machine learning: A review in the context of forest science
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Remotely Piloted Aircraft Systems (RPAS) and machine learning: A review in the context of forest science

Coelho Eugenio, Fernando ; Badin, Tiago Luis ; Fernandes, Pablo ; Mallmann, Caroline Lorenci ; Schons, Cristine ; Schuh, Mateus Sabadi ; Soares Pereira, Rudiney ; Fantinel, Roberta Aparecida ; Pereira da Silva, Sally Deborah

International journal of remote sensing, 2021-11, Vol.42 (21), p.8207-8235 [Periódico revisado por pares]

London: Taylor & Francis

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9
Effect of spring irrigation on soil salinity monitoring with UAV-borne multispectral sensor
Effect of spring irrigation on soil salinity monitoring with UAV-borne multispectral sensor
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Effect of spring irrigation on soil salinity monitoring with UAV-borne multispectral sensor

Yang, Ning ; Yang, Shuai ; Cui, Wenxuan ; Zhang, Zhitao ; Zhang, Junrui ; Chen, Junying ; Ma, Yu ; Lao, Congcong ; Song, Zhishuang ; Chen, Yinwen

International journal of remote sensing, 2021-12, Vol.42 (23), p.8952-8978 [Periódico revisado por pares]

London: Taylor & Francis

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10
A novel spectral-spatial multi-scale network for hyperspectral image classification with the Res2Net block
A novel spectral-spatial multi-scale network for hyperspectral image classification with the Res2Net block
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A novel spectral-spatial multi-scale network for hyperspectral image classification with the Res2Net block

Zhang, Zhongqiang ; Liu, Danhua ; Gao, Dahua ; Shi, Guangming

International journal of remote sensing, 2022-02, Vol.43 (3), p.751-777 [Periódico revisado por pares]

London: Taylor & Francis

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