Rodent Bones Classification Using Convolutional Neural Networks

Many researches of ornithologists are based on tracking the nutrition of their explored species of birds. This project assists the studying of nutrition patterns of raptors. Raptors are fed from various rodents. The bones of the rodents are indigestible and emitted out. By identifying the rodent species from its bone, one can learn about the nutrition pattern of the raptor. Classifying the rodent species requires high proficiency, and is a time-consuming process.
This project proposes an automatic machine which will determine the rodent species and the bone type, from a bone picture. This system will assist researchers as well as amateur birdwatchers (and many students who required to do the classification process).
The process will be held in two steps. First, a classification of the rodent type will be done through its jaw picture. Second, the rest of the bones in the pellet will be classified. [1]
The classification will be achieved using a convolutional neural network. The proposed system achieves about 96% success when classifying the rodent species, and about 88% success when classifying the rodent bone. In addition, further options to improve the system will be suggested.

Rodent Bones Classification
Rodent Bones Classification
Rodent Bones Classification Using Convolutional Neural Networks