Texture based Image Species Classification with Deep Convolutional Neural Network

被引:1
|
作者
Sharma, Geetanjali [1 ]
Krishna, C. Rama [1 ]
机构
[1] NITTTR, Dept Comp Sci Engn, Chandigarh, India
关键词
Texture Classification; Convolutional Neural Network (CNN); Deep Learning (DL); Shallow Learning (SL); Fine-tuning;
D O I
10.1109/i2ct45611.2019.9033881
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Our goal of study, texture based butterfly image classification with considering two standard deep learning networks and their shallower versions. Butterfly images involve only low and mid level texture information, which is typically learnt in the lower and mid-layers of the networks. We explore, whether smaller versions of these networks are robust enough to maintain a reasonable performance, as compared to the complete network, on the butterfly classification task. To identify the homogeneous texture region with texture class it belongs. We also demonstrate the effect of masking the background under the above scenario. Our approach yields high quality best results for the butterfly classification task, and we draw some interesting observations from our experimental analysis.
引用
收藏
页数:5
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