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A Review on Bird Classification on Different Dataset
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| Author:
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P. RANJITHA, M.U. ANUSHA, C. PRAGNA SHEKHAR, PRIYANKA P SHETTY, R. PUNEETHA
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| Abstract:
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The classification of bird species is an important task to perform, as they are important indicators of biodiversity. Previous studies on classification are effective only for a minimum amount of data set, since the classification was performed manually, the accuracy and precision with which the classification was performed is low. Therefore, an automatic classifier is necessary for bird classification. This article provides a novel approach to the description of bird species using various formats of data sets such as images, sounds and videos, and a comparative study on them. It is found that the classification based on visual characteristics is more effective and complex due to the problem it faces when processing them compared to the classification based on the phonetic sounds of the birds.
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| Keyword:
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Color Histograms, Convolution Neural Network, Data Mining, Support Vector Machine, Random Forest.
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| EOI:
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-
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| DOI:
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https://doi.org/10.31838/ijpr/2020.12.04.163
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| Download:
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