N
Natsuda Kaothanthong
Researcher at Sirindhorn International Institute of Technology
Publications - 27
Citations - 107
Natsuda Kaothanthong is an academic researcher from Sirindhorn International Institute of Technology. The author has contributed to research in topics: Computer science & Disjoint sets. The author has an hindex of 5, co-authored 21 publications receiving 72 citations. Previous affiliations of Natsuda Kaothanthong include Thammasat University & Tohoku University.
Papers
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Journal ArticleDOI
Distance interior ratio
TL;DR: A novel 2D shape signature named Distance Interior Ratio that utilizes intersection pattern of the distribution of line segments with the shape and a histogram alignment method for adjusting the interval of the histogram according to the distance distribution is proposed.
Journal ArticleDOI
A feature-word-topic model for image annotation and retrieval
TL;DR: This article proposes a novel method for image annotation based on combining feature-word distributions, which map from visual space to word space, and word-topic distributions, who form a structure to capture label relationships for annotation.
Journal ArticleDOI
Deep Learning for Anterior Segment Optical Coherence Tomography to Predict the Presence of Plateau Iris
Boonsong Wanichwecharungruang,Natsuda Kaothanthong,Warisara Pattanapongpaiboon,Pantid Chantangphol,Kasem Seresirikachorn,Chaniya Srisuwanporn,Nucharee Parivisutt,Andrzej Grzybowski,Thanaruk Theeramunkong,Paisan Ruamviboonsuk +9 more
TL;DR: In this paper, the authors evaluated the diagnostic performance of deep learning (DL) anterior segment optical coherence tomography (AS-OCT) as a plateau iris prediction model.
Proceedings ArticleDOI
A feature-word-topic model for image annotation
TL;DR: A novel method for image annotation based on feature-word and word-topic distributions with introduction of topics to efficiently take word associations, such as {ocean, fish, coral}, into image annotation.
Journal ArticleDOI
Algorithms for computing the maximum weight region decomposable into elementary shapes
Jinhee Chun,Natsuda Kaothanthong,Ryosei Kasai,Matias Korman,Martin Nöllenburg,Takeshi Tokuyama +5 more
TL;DR: This work considers the following geometric optimization problem: Given a weighted nxn pixel grid, find the maximum weight region whose shape is decomposable into a set of disjoint elementary shapes and gives efficient algorithms for several interesting shapes.