Bird species classification based on image using Convolutional Neural Network / Adam Izzat Azmi

Azmi, Adam Izzat (2024) Bird species classification based on image using Convolutional Neural Network / Adam Izzat Azmi. Degree thesis, Universiti Teknologi MARA, Terengganu.

Abstract

For numerous people nowadays, determining the species of birds and classifying them is getting challenging. To reliably describe bird species without relying on human labour, research has been done in this area. To identify and categorise bird species using digital images of their forms, colours, and patterns is the goal of this research. As part of the approach used in this project, a dataset of bird photos was gathered, the data was processed, and a Convolutional Neural Network model was trained to accurately identify and categorise the species of birds. The results of this study show the value of employing Convolutional Neural Network to identify birds because they successfully categorise birds in a variety of contexts with high accuracy rates. The actual work done includes data collecting from the Kaggle dataset, Convolutional Neural Network implementation, training the model, and performance evaluation. The acquired results demonstrate the potential of CNNs-based bird species categorization systems in raising interest in learning and increasing the success rate of monitoring bird populations. By offering fresh perspectives and approaches to the classification of bird species, this research advances the subject and creates new opportunities for global improvements in the study of animals. Finally, it is envisaged that the classification of bird species based on an image system will aid in expanding our understanding of and research into bird species, particularly in Malaysia.

Metadata

Item Type: Thesis (Degree)
Creators:
Creators
Email / ID Num.
Azmi, Adam Izzat
2022758409
Contributors:
Contribution
Name
Email / ID Num.
Thesis advisor
Ahmad, Khairul Adilah
UNSPECIFIED
Subjects: Q Science > QA Mathematics > Instruments and machines > Electronic Computers. Computer Science > Neural networks (Computer science)
Divisions: Universiti Teknologi MARA, Terengganu > Kuala Terengganu Campus > Faculty of Computer and Mathematical Sciences
Programme: Bachelor of Computer Science (Hons)
Keywords: Birds, Convolutional Neural Network model
Date: 2024
URI: https://ir.uitm.edu.my/id/eprint/95534
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