Vision System
Vision systems aim to replicate and enhance human vision capabilities using computational methods, primarily focusing on object detection, recognition, and tracking. Current research emphasizes improving accuracy and efficiency in challenging scenarios like camouflaged object detection and low-light conditions, often employing deep learning architectures such as YOLO and Vision Transformers, along with advancements in sensor technology like event cameras. These improvements have significant implications for diverse fields, including autonomous vehicles, industrial automation, healthcare, and ecological monitoring, by enabling more robust and reliable automated systems.
Papers
Towards an Autonomous Surface Vehicle Prototype for Artificial Intelligence Applications of Water Quality Monitoring
Luis Miguel Díaz, Samuel Yanes Luis, Alejandro Mendoza Barrionuevo, Dame Seck Diop, Manuel Perales, Alejandro Casado, Sergio Toral, Daniel Gutiérrez
Automated Quality Control System for Canned Tuna Production using Artificial Vision
Sendey Vera, Luis Chuquimarca, Wilson Galdea, Bremnen Véliz, Carlos Saldaña