Weight modulation in top–down computational model for target search
| Autor: | R. Aarthi, J. Amudha |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
010309 optics
Statistics and Probability Artificial Intelligence Computer science Modulation 0103 physical sciences 0202 electrical engineering electronic engineering information engineering General Engineering 020201 artificial intelligence & image processing 02 engineering and technology Topology 01 natural sciences |
| Zdroj: | Journal of Intelligent & Fuzzy Systems. 41:5411-5423 |
| ISSN: | 1875-8967 1064-1246 |
| DOI: | 10.3233/jifs-189863 |
| Popis: | Computer vision research aims at building models which mimic human systems. The recent development in visual information have been used to derive computational models which address a variety of applications. Biological models help to identify the salient objects in the image. But, the identification of non-salient objects in a heterogeneous environment is a challenging task that requires a better understanding of the visual system. In this work, a weight modulation based top-down model is proposed that integrates the visual features that depend on its importance for the target search application. The model is designed to learn the optimal weights such that it biases the features of the target from the other surrounding regions. Experimental analysis is performed on various scenes on a standard dataset with the selected object in the scene. Metrics such as area under curve, average hit number and correlation reveal that the method is more suitable in target identification, by suppressing the other region. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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