Piglets Detection and Counting using Deep Neural Networks
| Title | Piglets Detection and Counting using Deep Neural Networks |
|---|---|
| Summary | Piglets Detection and Counting using Deep Neural Networks |
| Keywords | |
| TimeFrame | Winter 2018, Spring 2019 |
| References | Yolo: https://pjreddie.com/darknet/yolo/ |
| Prerequisites | Artificial Intelligence and Learning Systems courses; good knowledge of machine learning and neural networks; python programming skills for implementing machine learning algorithms. |
| Author | |
| Supervisor | Peter Berck, Sepideh Pashami |
| Level | |
| Status |
Machine learning is being applied to all areas in society nowadays, and farming is no exception. Another are of deep learning which has gained a huge popularity the last years is image classification and object recognition. Better hardware and the availability of data has made the field of image processing the poster child for deep learning techniques.
This project combines smart farming with object recognition and. Its aim is to detect and count piglets from camera images, using semi-supervised learning and transfer learning. The work will involve finding appropriately labelled training data, training a detection network, and applying the trained network to the unlabelled data from the webcams.
This project needs to be done on-site at Sony in Lund (at least one day a week).
