2015
DOI: 10.1016/j.procs.2015.04.169
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Semantic Image Analysis for Intelligent Image Retrieval

Abstract: Image understanding and analysis is the most exciting and fastest-growing research areas in the computer vision. Recent computer vision technologies and algorithms are support efficient semantic image analysis and retrieval. Image analysis is deal with image representation, estimation formula, and sampling density. Image analysis at semantic level is result in automatic extraction of image descriptions as per human perception which ultimately bridge semantic gap between low-level visual features and the high-l… Show more

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Cited by 12 publications
(4 citation statements)
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“…We can extract higher-level image features. As we know, the human visual cortex is an excellent image analysis apparatus, human visual perception model is a basic inspiration of many image analysis tools such as edge detector, or neural network (Khodaskar & Ladhake, 2015). Simply, combining human visual capabilities and existing ground knowledge to analyse GEHRI using GEOBIA approaches supposed to be a good option for monitoring AWs in tropical peatlands.…”
Section: Previous Researches and Key Differencesmentioning
confidence: 99%
“…We can extract higher-level image features. As we know, the human visual cortex is an excellent image analysis apparatus, human visual perception model is a basic inspiration of many image analysis tools such as edge detector, or neural network (Khodaskar & Ladhake, 2015). Simply, combining human visual capabilities and existing ground knowledge to analyse GEHRI using GEOBIA approaches supposed to be a good option for monitoring AWs in tropical peatlands.…”
Section: Previous Researches and Key Differencesmentioning
confidence: 99%
“…Ates et al proposed a novel Markov random field (MRF) framework to improve the accuracy of image parsing [13]. Image analysis under the semantic level leads to automatic extraction of image descriptions based on human perception, finally bridges the semantic differences between low level image features and high-level concepts that capture conveyance [14].…”
Section: Introductionmentioning
confidence: 99%
“…It can be fixed or animated, colored or not, digital or not, real or virtual. Moreover, the image will make clinical diagnosis without recourse to any doctor, thanks to artificial intelligence [2]. The image is a didactic tool widely (and logically) used in the teaching of medicine.…”
Section: Introductionmentioning
confidence: 99%