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Reptile Recognition based on Convolutional Neural Network
Publication year - 2020
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.c1026.0193s20
Subject(s) - convolutional neural network , turtle (robot) , crocodile , kernel (algebra) , computer science , artificial intelligence , ecology , biology , mathematics , combinatorics
Indonesian people are less interested in reptile animals. These are because most Indonesian people have the mindset that reptiles are difficult to tame and are focused on things about the ferocity of these animals in their natural habitat. Therefore it is necessary to have the means to identify reptile objects as one of the educational tools for introducing reptiles to the public. This research aims to produce a specialized Convolutional Neural Network model for recognizing reptile species. We also expand the model for recognizing another reptile species such as Snake, Crocodile, Turtle, and Gecko. Thousands of reptile images are being trained inside our model in order to obtain a kernel that can be used to automate reptile species recognition based on ordinary camera images. Our model currently reaches 64.3% accuracy for detecting 14 different species. Finally, as a suggestion for the next research, further enrichment especially from the background extraction process is needed to increase the accuracy of reptile detection.

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