One Approach to intellectual image analysis
| Autor: | Olga Shemagina, Sergey Starkov, Nikolai Bellustin, Aleksandr Telnykh, Konstantin Moiseev |
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| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
Similarity (geometry)
lcsh:T58.5-58.64 business.industry lcsh:Information technology Semantic analysis (machine learning) ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Object (computer science) Image (mathematics) Set (abstract data type) Computer Science::Computer Vision and Pattern Recognition Computer Science::Programming Languages Computer vision Artificial intelligence business Mathematics |
| Zdroj: | ITM Web of Conferences, Vol 8, p 01010 (2016) |
| ISSN: | 2271-2097 |
| Popis: | This study investigated the method of semantic image analysis by using a set of neuron-like detectors of foreground objects. This method is intended to find different types of foreground objects and to determine properties of these objects. As a result of semantic analysis the semantic descriptor of the image is created. The descriptor is a set of foreground objects of the image and a set of properties for each object. The distance between images is defined as distance between their semantic descriptors. Using the concept of distance between images, “semantically similarity” between images or videos is defined. |
| Databáze: | OpenAIRE |
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