Classification of tourism categories based on heterogeneous features considering existence of reliable results

Naoki Saito; Takahiro Ogawa; Satoshi Asamizu; Miki Haseyama

doi:10.1117/12.2521056

22 March 2019 Classification of tourism categories based on heterogeneous features considering existence of reliable results

Naoki Saito, Takahiro Ogawa, Satoshi Asamizu, Miki Haseyama

Author Affiliations +

Proceedings Volume 11049, International Workshop on Advanced Image Technology (IWAIT) 2019; 1104905 (2019) https://doi.org/10.1117/12.2521056
Event: 2019 Joint International Workshop on Advanced Image Technology (IWAIT) and International Forum on Medical Imaging in Asia (IFMIA), 2019, Singapore, Singapore

Abstract

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.

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Naoki Saito, Takahiro Ogawa, Satoshi Asamizu, and Miki Haseyama "Classification of tourism categories based on heterogeneous features considering existence of reliable results", Proc. SPIE 11049, International Workshop on Advanced Image Technology (IWAIT) 2019, 1104905 (22 March 2019); https://doi.org/10.1117/12.2521056

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KEYWORDS

Image classification

Visualization

Statistical modeling

Convolution

Convolutional neural networks

Data modeling

Fuzzy logic

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