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    A combination of graph ranking and term collocation information for image annotation 

    Krittapad Suriya; Ohm Sornil (National Institute of Development Administration, 2006)

    In a large image database, an automatic image annotation plays an important role to assign a caption to an image. There are many applications of image annotation which include information extraction, knowledge acquisition, finding answers from specific questions, etc. In this research, we propose an image annotation approach using a graph ranking algorithm on a novel structure which includes similarities among regions within images and caption term collocation information. Caption terms are selected using a graph random walk method biased ...
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    Image parsing using local features of superpixels and genetic algorithm 

    Joseph, Ferdin Joe John; Surapong Auwatanamongkol (National Institute of Development Administration, 2014)

    Image porsing is a new avenue in the field of Computer Vision and Machine Learning. Similar to parsing of text into meaningful tokens and classifying them based on the user discretions, images are also parsed to understand the contents of the image. In this regard, there lies a need for image parsing systems to parse the images and understand the contents of the images in an efficient way. In the recent past various image parsing methodologies are proposed with huge fcaturc sct and ambiguity in performance based on class and pixels detected. Many ...