Supervisor

Dr. Muhammad Iqbal

Programme

BSc (Hons) in Computing in IT

Subject

Computer Science

Abstract

For our capstone project, we built a machine learning model that can look at pictures of dogs and figure out how they’re feeling, like if they’re happy, sad, or just chill. The idea came from how important pets are in people’s lives these days and how cool it would be to actually understand their emotions better using tech. This system will allow users to upload images of dogs, which are then analysed by a trained model to classify the dog's emotional states such as happy, sad, or neutral. We followed the CRISP-DM process to build it, which basically means we went through steps like understanding the goal, getting and cleaning data, training and testing the model, and thinking about how it could be used in real life. So the proposed fully trained model can be used in many ways. It can be used in the backend of a ‘Dog classification website’ or it can be a mobile application. It could help pet owners take better care of their pets, and maybe even help catch signs of stress or sadness early. This report is about how models are trained, what is used and how It shows how tech can actually help us connect better with our pets and understand them in a smarter way.

Date of Award

2025

Full Publication Date

2025

Access Rights

open access

Document Type

Dissertation

Resource Type

bachelor thesis

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