Plant Species Recognition using Bag-Of-Word with SVM Classifier in the Context of the LifeCLEF Challenge
نویسندگان
چکیده
For the plant task of the LifeCLEF challenge, we adopted the reference Bag-of-Word framework (BoW) with local soft assignment. The points of interests (POI) are both detected and described with the SIFT and OpponentColor SIFT. Parameters of the bag of word are optimized through cross-validation and we present the results of different experimentations. A Support Vector Machine is trained with different strategies according to the organs and species of plants.
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