Fredy Barrientos

Email: fredybar[at]ucm[dot]es
Phone: (+34) 91 394 4375
Room: Physics - 237

Bio

Hi! I'm a PhD student in Computer Science and Engineering at Complutense University of Madrid (UCM), in the Systems Engineering, Control, Automation and Robotics (ISCAR) Research Group, with Professor Gonzalo Pajares and Eva Besada.
I completed my Master in Computer Science and Engineering at University of Deusto where I was advised by Professor Enrique Onieva. I completed my Bachelor in Systems Engineering at National University of San Cristóbal de Huamanga.

My research focuses on building deep learning algorithms for object detection and semantic segmentation within the AMPBAS project (Automatic Monitoring of Pollutants in Dammed Waters using Biosensors and Autonamous Surface Vehicle, 2019-2021, RTI2018-098962-B-C21) and AI-GES-BLOOM-CM (Towards an integrated system for the warning and management of cyanobacterial BLOOMs in inland waters, 2021-2024, SINERGICOS-CAM UAM-UCM).

Publications

  • Jun. 2024: Customization of the Text-to-Image Diffusion Model by Fine-Tuning for the generation of synthetic images of cyanobacterial blooms in lentic water bodies (Under Review)]
  • Jun. 2024: Integration of object detection and semantic segmentation based on Convolutional Neural Networks for navigation and monitoring of cyanobacterial blooms in lentic water scenes [Applied Soft Computing (Accepted and published)][paper]
  • Nov. 2023: Filter Pruning for Convolutional Neural Networks in Semantic Image Segmentation [Neural Networks (Accepted and published)][paper]
  • Apr. 2023: Semantic segmentation based on Deep learning for the detection of Cyanobacterial Harmful Algal Blooms (CyanoHABs) using synthetic images [Applied Soft Computing (Accepted and published)][paper]

Projects

  • SMART-BLOOMS (TED2021-130123B-I00) from the MCIN/AEI/10.13039/501100011033 and NextGenerationEU/PRTR programs.
  • AI-GES-BLOOM-CM: Towards an integrated system for the warning and management of cyanobacterial BLOOMs in inland waters, 2021-2024, SINERGICOS-CAM UAM-UCM.
  • AMPBAS: Automatic Monitoring of Pollutants in Dammed Waters using Biosensors and Autonamous Surface Vehicle, 2019-2021, RTI2018-098962-B-C21.

Blog

In construction.