Piglets Detection and Counting using Deep Neural Networks

From ISLAB/CAISR
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 Master
Status Open

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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).