Classification of tourism categories based on heterogeneous features considering existence of reliable results
Naoki Saito, Takahiro Ogawa, Satoshi Asamizu, Miki Haseyama · International Workshop on Advanced Image Technology (IWAIT) 2019 · 2019
This paper presents a classification method of tourism categories based on heterogeneous features considering existence of reliable results. The proposed method performs estimation of existence of reliable results based on one-versus-one scheme from three kinds of classification results obtained from tourism images, geotags and textual tags, separately. Then if the reliable result is included in the above results, this result is regarded as a final result. Otherwise, the final result is obtained by the multiple annotator logistic regression. The proposed method realizes accurate classification by estimating the existence of reliable results from more than two kinds of results.