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EXPLORING GROUND SEGMENTATION FROM LIDAR SCANNING-DERIVED IMAGES USING CONVOLUTIONAL NEURAL NETWORKS.
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- International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences, 2023, v. 48, n. 1/W1, p. 221, doi. 10.5194/isprs-archives-XLVIII-1-W1-2023-221-2023
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USING DEEP LEARNING TO DIGITIZE ROAD ARROW MARKINGS FROM LIDAR POINT CLOUD DERIVED IMAGES.
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- International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences, 2020, v. 43, n. B5, p. 123, doi. 10.5194/isprs-archives-XLIII-B5-2020-123-2020
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A PRELIMINARY STUDY ON UPDATING HIGH DEFINITION MAPS: DETECTING AND POSITIONING A TRAFFIC CONE BY USING A STEREO CAMERA.
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- International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences, 2019, v. XLII-4/W19, p. 271, doi. 10.5194/isprs-archives-XLII-4-W19-271-2019
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USING OPENLY SOURCED 3D GEOGRAPHIC INFORMATION SYSTEMS (GIS) IN DETERMINING THE PHOTOVOLTAIC POTENTIAL OF QUEZON CITY HALL IN TERMS OF RECEIVED DIRECT SOLAR RADIATION.
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- International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences, 2019, v. XLII-4/W19, p. 263, doi. 10.5194/isprs-archives-XLII-4-W19-263-2019
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- Article
BOOSTING U-NET WITH FOCAL LOSS FOR ROAD MARKING CLASSIFICATION ON SPARSE MOBILE LIDAR POINT CLOUD DERIVED IMAGES.
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- ISPRS Annals of Photogrammetry, Remote Sensing & Spatial Information Sciences, 2022, n. 5, p. 33, doi. 10.5194/isprs-annals-V-5-2022-33-2022
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