Email
DNINFOA - SIA
Libraries
Calls
UNAL identity
Research line
Smart sensing and environment perception
We develop sensing, signal processing and artificial intelligence techniques to observe and interpret complex environments.
We develop sensing, signal processing and artificial intelligence techniques to observe, characterize and interpret complex environments. We integrate imagery, IoT sensors, aerial platforms and radar technologies for applications ranging from precision agriculture to buried object detection and humanitarian demining.
Topics
Radar, sensing and artificial intelligence9 works
We develop radar and Ground Penetrating Radar (GPR) techniques combined with signal processing, machine learning and deep learning to detect, classify and characterize phenomena and objects. We study both the acquisition systems (antennas, time response and group delay) and the computational methods to extract information from signals, images and spatio-temporal data.
Faculty
Active students
Recent work
RGB, multispectral and hyperspectral imaging5 works
We research image acquisition, processing and analysis techniques for automatic information extraction, using computer vision, feature descriptors and deep learning. Applications include crop characterization, weed detection and quantification, and object detection and classification in mobility scenarios.
Precision agriculture6 works
We develop computer vision, multispectral image processing and deep learning methods to characterize crops and automate agricultural tasks, particularly weed detection, classification and quantification. This work combines spectral and spatial information with pattern recognition techniques to support crop monitoring and management.
Timeline
2026
2025
2023
2022
2021
- Locating Ships Using Time Reversal and Matrix Pencil Method by Their Underwater Acoustic Signals
- Método para la estimación de maleza en cultivos de lechuga utilizando aprendizaje profundo e imágenes multiespectrales
- Monitoring of the refractory lining in a shielded electric arc furnace: An online multitarget regression trees approach
- Temperature Prediction Using Multivariate Time Series Deep Learning in the Lining of an Electric Arc Furnace for Ferronickel Production
2020
- A Deep Learning Approach for Weed Detection in Lettuce Crops Using Multispectral Images
- Cost-Effective Implementation of a Temperature Traceability System Based on Smart RFID Tags and IoT Services
- Damage Identification in Structural Health Monitoring: A Brief Review from its Implementation to the Use of Data-Driven Applications
2019
2018