Jorge Torres-Sánchez
Orcid: 0000-0003-1420-0145
According to our database1,
Jorge Torres-Sánchez
authored at least 16 papers
between 2015 and 2023.
Collaborative distances:
Collaborative distances:
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Bibliography
2023
Mobile terrestrial laser scanner <i>vs</i>. UAV photogrammetry to estimate woody crop canopy parameters - Part 2: Comparison for different crops and training systems.
Comput. Electron. Agric., September, 2023
Mobile terrestrial laser scanner vs. UAV photogrammetry to estimate woody crop canopy parameters - Part 1: Methodology and comparison in vineyards.
Comput. Electron. Agric., September, 2023
2021
Grape Cluster Detection Using UAV Photogrammetric Point Clouds as a Low-Cost Tool for Yield Forecasting in Vineyards.
Sensors, 2021
2020
Classification of 3D Point Clouds Using Color Vegetation Indices for Precision Viticulture and Digitizing Applications.
Remote. Sens., 2020
Monitoring Vineyard Canopy Management Operations Using UAV-Acquired Photogrammetric Point Clouds.
Remote. Sens., 2020
Mapping Cynodon Dactylon Infesting Cover Crops with an Automatic Decision Tree-OBIA Procedure and UAV Imagery for Precision Viticulture.
Remote. Sens., 2020
2018
An Automatic Random Forest-OBIA Algorithm for Early Weed Mapping between and within Crop Rows Using UAV Imagery.
Remote. Sens., 2018
3-D Characterization of Vineyards Using a Novel UAV Imagery-Based OBIA Procedure for Precision Viticulture Applications.
Remote. Sens., 2018
2016
Selecting patterns and features for between- and within- crop-row weed mapping using UAV-imagery.
Expert Syst. Appl., 2016
Proceedings of the 2016 IEEE Symposium Series on Computational Intelligence, 2016
2015
Quantifying Efficacy and Limits of Unmanned Aerial Vehicle (UAV) Technology for Weed Seedling Detection as Affected by Sensor Resolution.
Sensors, 2015
Spatial Quality Evaluation of Resampled Unmanned Aerial Vehicle-Imagery for Weed Mapping.
Sensors, 2015
Assessing Optimal Flight Parameters for Generating Accurate Multispectral Orthomosaicks by UAV to Support Site-Specific Crop Management.
Remote. Sens., 2015
An automatic object-based method for optimal thresholding in UAV images: Application for vegetation detection in herbaceous crops.
Comput. Electron. Agric., 2015
A semi-supervised system for weed mapping in sunflower crops using unmanned aerial vehicles and a crop row detection method.
Appl. Soft Comput., 2015
An Experimental Comparison for the Identification of Weeds in Sunflower Crops via Unmanned Aerial Vehicles and Object-Based Analysis.
Proceedings of the Advances in Computational Intelligence, 2015