Global Wheat Detection
- 0 Collaborators
Showcases the use of deep learning to detect wheat heads from crops. ...learn more
Project status: Under Development
Internet of Things, Artificial Intelligence
Intel Technologies
Intel Python
Overview / Usage
The project is based on this Kaggle Competition: https://www.kaggle.com/c/global-wheat-detection. The task is to detect wheat heads from outdoor images of wheat plants, including wheat datasets from around the globe. Using worldwide data, you will focus on a generalized solution to estimate the number and size of wheat heads. To better gauge the performance for unseen genotypes, environments, and observational conditions, the training dataset covers multiple regions. You will use more than 3,000 images from Europe (France, UK, Switzerland) and North America (Canada). The test data includes about 1,000 images from Australia, Japan, and China.
Methodology / Approach
Uses deep learning-based object detection models like Faster R-CNN for the detection task.
Technologies Used
- TensorFlow Object Detection API