José M. Peña

According to our database1, José M. Peña authored at least 19 papers between 2008 and 2020.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.



In proceedings 
PhD thesis 





Mapping Cynodon Dactylon Infesting Cover Crops with an Automatic Decision Tree-OBIA Procedure and UAV Imagery for Precision Viticulture.
Remote. Sens., 2020

Comparing UAV-Based Technologies and RGB-D Reconstruction Methods for Plant Height and Biomass Monitoring on Grass Ley.
Sensors, 2019

Watson on the Farm: Using Cloud-Based Artificial Intelligence to Identify Early Indicators of Water Stress.
Remote. Sens., 2019

An Automatic Random Forest-OBIA Algorithm for Early Weed Mapping between and within Crop Rows Using UAV Imagery.
Remote. Sens., 2018

Mapping Crop Calendar Events and Phenology-Related Metrics at the Parcel Level by Object-Based Image Analysis (OBIA) of MODIS-NDVI Time-Series: A Case Study in Central California.
Remote. Sens., 2018

3-D Characterization of Vineyards Using a Novel UAV Imagery-Based OBIA Procedure for Precision Viticulture Applications.
Remote. Sens., 2018

Selecting patterns and features for between- and within- crop-row weed mapping using UAV-imagery.
Expert Syst. Appl., 2016

Machine learning paradigms for weed mapping via unmanned aerial vehicles.
Proceedings of the 2016 IEEE Symposium Series on Computational Intelligence, 2016

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

Object-Based Image Classification of Summer Crops with Machine Learning Methods.
Remote. Sens., 2014

Semiautomatic Detection of Artificial Terrestrial Targets for Remotely Sensed Image Georeferencing.
IEEE Geosci. Remote. Sens. Lett., 2013

Parameter estimation of q-Gaussian Radial Basis Functions Neural Networks with a Hybrid Algorithm for binary classification.
Neurocomputing, 2012

A logistic radial basis function regression method for discrimination of cover crops in olive orchards.
Expert Syst. Appl., 2010

Feature Selection for Hybrid Neuro-Logistic Regression Applied to Classification of Remote Sensed Data.
Proceedings of the 8th International Conference on Hybrid Intelligent Systems (HIS 2008), 2008