Preprint Article Version 1 This version is not peer-reviewed

Modified Deep Neural Networks for Dog Breeds Identification

Version 1 : Received: 17 December 2018 / Approved: 19 December 2018 / Online: 19 December 2018 (07:57:03 CET)

How to cite: Ayanzadeh, A.; Vahidnia, S.. Modified Deep Neural Networks for Dog Breeds Identification. Preprints 2018, 2018120232 (doi: 10.20944/preprints201812.0232.v1). Ayanzadeh, A.; Vahidnia, S.. Modified Deep Neural Networks for Dog Breeds Identification. Preprints 2018, 2018120232 (doi: 10.20944/preprints201812.0232.v1).

Abstract

In this paper, we leverage state of the art models on Imagenet data-sets. We use the pre-trained model and learned weighs to extract the feature from the Dog breeds identification data-set. Afterwards, we applied fine-tuning and dataaugmentation to increase the performance of our test accuracy in classification of dog breeds datasets. The performance of the proposed approaches are compared with the state of the art models of Image-Net datasets such as ResNet-50, DenseNet-121, DenseNet-169 and GoogleNet. we achieved 89.66% , 85.37% 84.01% and 82.08% test accuracy respectively which shows the superior performance of proposed method to the previous works on Stanford dog breeds datasets.

Supplementary and Associated Material

Subject Areas

Computer vision, Data Augmentation, Fine- Tuning, Imagenet

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our diversity statement.

Leave a public comment
Send a private comment to the author(s)
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.