Wolf and Dog Breed Image Classification Using Deep Learning Techniques

Chaturvedi, Kumar (2020) Wolf and Dog Breed Image Classification Using Deep Learning Techniques. Masters thesis, Dublin, National College of Ireland.

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Abstract

A huge money is involved in pet insurance and medical treatments of pets. Missing pet is a global issue also rescue teams face a lot of challenges while rescuing pets since sometimes they encounter wolfs also which looks same as dogs. For this purpose, new dataset has been created by combining Stanford dog dataset and wolf images from kaggle. Transfer learning technique has been used in this work by using pretrained convolutional networks like ResNet101, ResNet50, VGG16, VGG19, DenseNet201etc. These models can help in distinguishing between wolf and different dog breeds. For evaluating model’s accuracy and model loss metrices has been used. ResNet101 performed better than all other transfer learning techniques and achieved 90.80% accuracy. Many state-of-the-art researches were considered and this work with new dataset of wolf and dog images performed well. One CNN model has also been created which also performed better and further accuracy can be improved by training with more images.

Item Type:	Thesis (Masters)
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > QA Mathematics > Computer software T Technology > T Technology (General) > Information Technology > Computer software
Depositing User:	Dan English
Date Deposited:	22 Jan 2021 11:09
Last Modified:	22 Jan 2021 11:09
URI:	https://norma.ncirl.ie/id/eprint/4435

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