Abstract
In this paper, we address the image region tagging procedure in which each image region is annotated by a suitable concept. Specifically, we first extract the feature vector for each segmented region. Then we propose a Genetic Algorithm (GA)-based simultaneous classifier and feature selection method working with ensemble system to learn the relationship between the low-level features and high-level concepts. The extensive experiments conducted on two public datasets namely MSRC v1 and MSRC v2 demonstrate the better performance of our method than several well-known ensemble methods, supervised machine learning methods, and sparse coding-based methods in the regions-in-image classification task.
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Luong, A.V., Nguyen, T.T., Pham, X.C., Nguyen, T.T.T., Liew, A.WC., Stantic, B. (2018). Automatic Image Region Annotation by Genetic Algorithm-Based Joint Classifier and Feature Selection in Ensemble System. In: Nguyen, N., Hoang, D., Hong, TP., Pham, H., Trawiński, B. (eds) Intelligent Information and Database Systems. ACIIDS 2018. Lecture Notes in Computer Science(), vol 10751. Springer, Cham. https://doi.org/10.1007/978-3-319-75417-8_56
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