Showcases the use of deep learning to detect wheat heads from crops. The project is based on: https://www.kaggle.com/c/global-wheat-detection.
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Updated
May 30, 2020 - Jupyter Notebook
Showcases the use of deep learning to detect wheat heads from crops. The project is based on: https://www.kaggle.com/c/global-wheat-detection.
Wheat detection using Faster RCNN
Detecting wheat heads using YOLOv5
🌾 Wheat Detection using YOLO11n! 📸 Installs Ultralytics, trains on GlobalWheat2020 dataset, and detects wheat heads with bounding boxes. Includes dataset setup, model training, and inference. 🚀
Global wheat detection using YOLOv2 in Keras.
This is the training notebook of my EfficienDet solution to the Global Wheat Detection competition on Kaggle.
This is a hybrid variety of detection models which is inspired from bothe centrenet and EfficientDet. This model is as fast as centrenet and much accurate due to the fusion blocks.
Wheat heads detection using Faster-RCNN in pytorch
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