tyrerodr
Greetings! I'm a dedicated Computer Science Engineer with a strong passion for computer vision technologies and problem-solving.
Ecuador
Pinned Repositories
Caso-de-estudio-redes
BirdAudioClassificationProsperina
Using TensorFlow, Keras, & VAEs, we classify bird sounds in Bosque Protector La Prosperina. Leveraging Deep Learing & audio expertise to enhance avian biodiversity understanding.
CIIFEN-PluviogramDigitizer
CRUDSQLSERVER-LIBRARY
Proyecto CRUD desarrollado en Python con Librería PYQT5, con conexión a SQLSERVER
Edamatel-Website
GreenAreaDetectionWithDrones
This project uses U-Net with EfficientNetB3 for semantic segmentation to detect and quantify green areas in high-resolution aerial images. Transfer learning enhances accuracy, processing 6000x4000 pixel images from altitudes of 5 to 30 meters. It also calculates percentages of vegetation cover from the binary mask generated.
RealTimeDrowsyDrivingDetection
The Drowsiness Detection System uses YOLOv8 models to monitor drowsiness in real-time by detecting eye states and yawning. Built with Python and leveraging the GroundingDINO library for bounding box generation, this project offers real-time alerts through a PyQt5 interface.
tyrerodr's Repositories
tyrerodr/BirdAudioClassificationProsperina
Using TensorFlow, Keras, & VAEs, we classify bird sounds in Bosque Protector La Prosperina. Leveraging Deep Learing & audio expertise to enhance avian biodiversity understanding.
tyrerodr/CIIFEN-PluviogramDigitizer
tyrerodr/CRUDSQLSERVER-LIBRARY
Proyecto CRUD desarrollado en Python con Librería PYQT5, con conexión a SQLSERVER
tyrerodr/Edamatel-Website
tyrerodr/GreenAreaDetectionWithDrones
This project uses U-Net with EfficientNetB3 for semantic segmentation to detect and quantify green areas in high-resolution aerial images. Transfer learning enhances accuracy, processing 6000x4000 pixel images from altitudes of 5 to 30 meters. It also calculates percentages of vegetation cover from the binary mask generated.
tyrerodr/RealTimeDrowsyDrivingDetection
The Drowsiness Detection System uses YOLOv8 models to monitor drowsiness in real-time by detecting eye states and yawning. Built with Python and leveraging the GroundingDINO library for bounding box generation, this project offers real-time alerts through a PyQt5 interface.