Pinned Repositories
Dashcam_vehicle_detection
This repository contains a comprehensive system designed to detect vehicles in dashcam videos using HOG features. Leveraging traditional computer vision techniques, the project showcases a robust pipeline that encompasses feature extraction, image processing, and sliding window-based detection.
ELP
Ensemble Learning Project - MSc AI - CS
Player_detection
This POC repository showcases the use of the YOLOv8 model for the purpose of detecting and tracking players in field hockey videos. The focus is on analyzing footage from the French Elite Championship.
Player_segmentation
Football player segmentation project with images from the Kaggle dataset "⚽ Football Player Segmentation ⚽" to use this model to create a Hockey or "all-sports" player segmentation dataset.
Satellite_flood_segmentation
Optical Satellite Flood Segmentation: A deep learning approach to segment and identify flooded areas using optical satellite imagery. This project contains a notebook, models, datasets, and evaluation tools used for a Kaggle competition.
FoodSAM
FoodSAM: Any Food Segmentation
FoodSeg103-Benchmark-v1
MM'21 Main-Track paper
GiraudJules's Repositories
GiraudJules/Player_detection
This POC repository showcases the use of the YOLOv8 model for the purpose of detecting and tracking players in field hockey videos. The focus is on analyzing footage from the French Elite Championship.
GiraudJules/Dashcam_vehicle_detection
This repository contains a comprehensive system designed to detect vehicles in dashcam videos using HOG features. Leveraging traditional computer vision techniques, the project showcases a robust pipeline that encompasses feature extraction, image processing, and sliding window-based detection.
GiraudJules/ELP
Ensemble Learning Project - MSc AI - CS
GiraudJules/Player_segmentation
Football player segmentation project with images from the Kaggle dataset "⚽ Football Player Segmentation ⚽" to use this model to create a Hockey or "all-sports" player segmentation dataset.
GiraudJules/Satellite_flood_segmentation
Optical Satellite Flood Segmentation: A deep learning approach to segment and identify flooded areas using optical satellite imagery. This project contains a notebook, models, datasets, and evaluation tools used for a Kaggle competition.