Details
Status: Available
Type(s): Bachelor Thesis, Master Thesis, or Practicum
Participants: 1 Student
Keywords: Computer Vision, Image Classification, Deep Learning
Task Description & Requirements
Develop a deep classifier that is able to identify strongly camouflaged animals in images. The classifier should run on an embedded system (practically, a Raspberry Pi 4; edge computing) and employ an existing object classifier that is re-trained to the specific task (transfer learning). Once recognized, the classifier should be able to determine if, in case a bullet would go through the center of the image, the animal would be killed, wounded or remain unharmed. Based on the classification result, a hash value should be computed that can be read from the edge computer via an Android mobile app and forwarded to a given REST interface. Requires good deep learning skills, experience with edge computing and a minimal knowledge of mobile app programming.