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DOI: 10.14569/IJACSA.2020.0110840
PDF

Recognition of Local Birds of Bangladesh using MobileNet and Inception-v3

Author 1: Md. Mahbubur Rahman
Author 2: Al Amin Biswas
Author 3: Aditya Rajbongshi
Author 4: Anup Majumder

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 11 Issue 8, 2020.

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Abstract: Recognition of bird species can be a challenging task due to various complex factors. The purpose of this work is to distinguish various local bird species of Bangladesh from the image data. The MobileNet and Inception-v3 model which is mainly an image classification model used here to accomplish this work. Here, we have used a total of four approaches namely Inception-v3 without transfer learning, Inception-v3 with transfer learning, MobileNet without transfer learning, and MobileNet with transfer learning to accomplish the task. To evaluate our experimental results, we have calculated F1 Score besides the model’s accuracy and also presented the ROC curve to evaluate the model’s output quality. Then we have done a comparison among the applied four approaches. The experimental result has proved the working capability of the applied four approaches. Among these four approaches, MobileNet with transfer learning outperforms the others and obtained a test accuracy of 91.00%. For each of the classes, MobileNet with transfer learning obtained the highest F1 Score than other approaches.

Keywords: Recognition; MobileNet; Inception-v3; transfer learning; computer vision; Bangladeshi bird

Md. Mahbubur Rahman, Al Amin Biswas, Aditya Rajbongshi and Anup Majumder, “Recognition of Local Birds of Bangladesh using MobileNet and Inception-v3” International Journal of Advanced Computer Science and Applications(IJACSA), 11(8), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110840

@article{Rahman2020,
title = {Recognition of Local Birds of Bangladesh using MobileNet and Inception-v3},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0110840},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0110840},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {8},
author = {Md. Mahbubur Rahman and Al Amin Biswas and Aditya Rajbongshi and Anup Majumder}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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