The week's pick
Reseach Article
Analysis of Learning Techniques: Bird Species Classification
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 178 - Number 17 |
| Year of Publication: 2019 |
| Authors: Pranav Kumar Rai, Sourvi Chaturvedi, Sandhya Katiyar |
10.5120/ijca2019918969
|
Pranav Kumar Rai, Sourvi Chaturvedi, Sandhya Katiyar . Analysis of Learning Techniques: Bird Species Classification. International Journal of Computer Applications. 178, 17 ( Jun 2019), 12-16. DOI=10.5120/ijca2019918969
Abstract
Identification of bird species is a difficult problem that pushes the limits of the visual abilities for both humans and computers. Although different bird species share the same basic set of parts, different bird species can vary dramatically in shape and appearance[5]. Sometimes professional bird watchers disagree on the species given an image of a bird. Intra-class variance is high due to variation in lighting and background and extreme variation in pose (e.g., flying birds, swimming birds, and perched birds that are partially occluded by branches). In this paper, a simple image recognition classifier has been created. This image recognition tool classifies various species of birds. An application CNN has been used in order to extract features from the input image. Convolution preserves the spatial relationship between pixels by learning image features using small squares of input data. Then application of some of the supervised and unsupervised algorithms is used to check and compare their accuracies against each other. The aim is to find which learning algorithm’s accuracy is best in predicting a particular specie of bird given any image of it.
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