Arokamal/Team-3-Wheat-Detection

Wheat Detection mini project, for Omdena Algeria Chapter 2022 # Team-3-Wheat-Detection First Challenge: Wheat Detection mini project, given by Omdena Algeria Chapter 2022 🌾Wheat Detection🌾 Problem Statement: Detection of wheat heads is an important task allowing to estimate pertinent traits including head population density and head characteristics such as sanitary state, size, maturity stage and the presence of awns. Several studies developed methods for wheat head detection from high-resolution RGB imagery. They are based on computer vision and machine learning and are generally calibrated and validated on limited datasets. However, variability in observational conditions, genotypic differences, development stages, head orientation represents a challenge in computer vision. Further, possible blurring due to motion or wind and overlap between heads for dense populations make this task even more complex. Contributors: Searching for Dataset - Arokamal Sethy & Guindo Sadio Research on related works - Moumni samir & Hazem Searching for methods and algorithms - Nirmit Shah & Abhijeet Pundkar Implementation of EDA - Arokamal Sethy, Nirmit Shah & Abhijeet Pundkar Implementation of model and prediction - Arokamal Sethy Presentation & Documentation - Arokamal Sethy, Moumni Samir , Nirmit Shah & Abhijeet Pundkar