Animal identification and emotion detection using deep convolutional neural networks

According to a recent report, when it comes to animal protection laws Canada has not been performing adequately, receiving a grade of “D” on the Animal Protection Index (API). The low marks received were for not having adequate legislation protecting wildlife in captivity, working animals, farm animals, animals used in research and companion animals. At the same time, public support for improving animal welfare is high. In an effort to address this, we propose mobile application to identify animals and understand their emotions, which will utilize state-of-the-art convolutional neural networks. This solution will have a wide range of applications such as assisting in finding lost pets, preventing undesired animal trading, diagnosing emotional wellbeing of animals, and helping humans and wildlife to coexist by allowing humans to identify individual animals that frequent their communities or properties.

Faculty Supervisor:

Loutfouz Zaman

Student:

Partner:

Petnerup Inc.

Discipline:

Computer science

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

University of Ontario Institute of Technology

Program: