Coleoptera Classification Using Convolutional Neural Network and Transfer Learning

Coleoptera Classification Using Convolutional Neural Network and Transfer Learning
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© 2021 by IJETT Journal
Volume-69 Issue-5
Year of Publication : 2021
Authors : Jan Carlo T. Arroyo
DOI :  10.14445/22315381/IJETT-V69I5P201

How to Cite?

Jan Carlo T. Arroyo, "Coleoptera Classification Using Convolutional Neural Network and Transfer Learning," International Journal of Engineering Trends and Technology, vol. 69, no. 5, pp. 1-5, 2021. Crossref, https://doi.org/10.14445/22315381/IJETT-V69I5P201

Abstract
This study presents the use of convolutional neural networks and transfers learning for classifying Coleoptera specimens. The images used as a dataset in this study were gathered from previous research work and various repositories. Four classes were used to train the convolutional neural network, with the Buprestidae, Carabidae, Cerambycidae, and Coccinellidae families. Since the dataset was rather imbalanced, images were preprocessed to augment the dataset and minimize the probability of overfitting. Transfer learning was implemented by using the InceptionV3 pre-trained model. The final layer was retrained using the new dataset while retaining its prior knowledge base. After the training and validation of the new model, an average of 97% classification accuracy was attained.

Keywords
Beetle Classification, Coleoptera, Convolutional Neural Network, Inception Network, Transfer Learning

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