Lovebird image classification based on convolutional neural network

Abstract

Lovebird is a type of bird from the Psittacidae family, consisting of 90 generations. One of them is the genus Agapornis Selby or Lovebird, which has 9 species. In recognizing the differences of each species, you can use the Object Recognition system. One of them uses the popular CNN algorithm. The dataset was obtained from open sources totaling 8,992 datasets from 9 Agapornis species. It consists of 80% training images and 20% testing images from several datasets. After 10 accuracy tests, the results stated that the accuracy rate reached 89%. In addition, there are also extraction features extracted from images including color, shape, size, and texture characteristics. The things extracted in this study include the Mean, Standard Deviation, Kurtosis, Skewness, Variance, Entropy Value, Maximum Pixel, and Minimum Pixel.

Keywords

• lovebird
• agapornis
• classification
• cnn