| 期刊全稱 | Bayesian Approach to Image Interpretation | | 影響因子2023 | Sunil K. Kopparapu,Uday B. Desai | | 視頻video | http://file.papertrans.cn/182/181828/181828.mp4 | | 學(xué)科分類 | The Springer International Series in Engineering and Computer Science | | 圖書封面 |  | | 影響因子 | .Bayesian Approach to Image Interpretation. will interestanyone working in image interpretation. It is complete in itself andincludes background material. This makes it useful for a novice aswell as for an expert. It reviews some of the existing probabilisticmethods for image interpretation and presents some new results.Additionally, there is extensive bibliography covering references invaried areas. .For a researcher in this field, the material on synergisticintegration of segmentation and interpretation modules and theBayesian approach to image interpretation will be beneficial. .For a practicing engineer, the procedure for generating knowledgebase, selecting initial temperature for the simulated annealingalgorithm, and some implementation issues will be valuable. .New ideas introduced in the book include: . . Newapproach to image interpretation using synergism between thesegmentation and the interpretation modules. .. A new segmentationalgorithm based on multiresolution analysis. .. Novel use of theBayesian networks (causal networks) for image interpretation. ..Emphasis on making the interpretation approach less dependent on theknowledge base and hence more reliable by modeling | | Pindex | Book 2000 |
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