An Efficient Classification Algorithm on Orchid Species Based on Data Enhancement
1
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
In order to address the issue of low accuracy rate of current orchid type classification methods due to theirsimilarities in the characteristics of orchid types, an effective orchid type classification method using dataenhancement is suggested in this work, whose contribution depends on the utilization of data enhancementtechnologies, which can efficiently enhance the orchid type classification accuracy rate by providing sufficientand balanced sample sets. Specifically, in our approach, firstly, an image set of 12 orchid types containing12,227 images is established; secondly, the characteristics of the above orchid image dataset are analyzed andstudied; thirdly, the reasons for the processing difficulties are identified based on the above orchid image set;at last, some data enhancement technologies are applied to improve the classification accuracy rate of orchidtypes, which can also enhance the whole performance of orchid type classification. The experimental resultsdisplay that our suggested classification method using data enhancement in the article can achieve aclassification accuracy of 92.65% compared with the one not using data enhancement under the condition ofinsufficient and unbalanced image datasets.
Abstract
In order to address the issue of low accuracy rate of current orchid type classification methods due to theirsimilarities in the characteristics of orchid types, an effective orchid type classification method using dataenhancement is suggested in this work, whose contribution depends on the utilization of data enhancementtechnologies, which can efficiently enhance the orchid type classification accuracy rate by providing sufficientand balanced sample sets. Specifically, in our approach, firstly, an image set of 12 orchid types containing12,227 images is established; secondly, the characteristics of the above orchid image dataset are analyzed andstudied; thirdly, the reasons for the processing difficulties are identified based on the above orchid image set;at last, some data enhancement technologies are applied to improve the classification accuracy rate of orchidtypes, which can also enhance the whole performance of orchid type classification. The experimental resultsdisplay that our suggested classification method using data enhancement in the article can achieve aclassification accuracy of 92.65% compared with the one not using data enhancement under the condition ofinsufficient and unbalanced image datasets.