FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2289009511> ?p ?o ?g. }

• W2289009511 abstract "This dissertation concerns the development of an interactive machine learning method for refinement and analysis of segmented computed tomography (CT) images. This method uses higher-level domain-dependent knowledge to improve initial image segmentation results. A knowledge-based refinement and analysis system requires the formulation of domain knowledge. A serious problem faced by knowledge-based system designers is the knowledge acquisition bottleneck. Knowledge acquisition is very challenging and an active research topic in the field of machine learning and artificial intelligence. Commonly, a knowledge engineer needs to have a domain expert to formulate acquired knowledge for use in an expert system. That process is rather tedious and error-prone. The domain expert's verbal description can be inaccurate or incomplete, and the knowledge engineer may not correctly interpret the expert's intent. In many cases, the domain experts prefer to do actions instead of explaining their expertise. These problems motivate us to find another solution to make the knowledge acquisition process less challenging. Instead of trying to acquire expertise from a domain expert verbally, we can ask him/her to show expertise through actions that can be observed by the system. If the system can learn from those actions, this approach is called learning by demonstration. We have developed a system that can learn region refinement rules automatically. The system observes the steps taken as a human user interactively edits a processed image, and then infers rules from those actions. During the system's learn mode, the user views labeled images and makes refinements through the use of a keyboard and mouse. As the user manipulates the images, the system stores information related to those manual operations, and develops internal rules that can be used later for automatic postprocessing of other images. After one or more training sessions, the user places the system into its run mode. The system then accepts new images, and uses its rule set to apply postprocessing operations automatically in a manner that is modeled after those learned from the human user. At any time, the user can return to learn mode to introduce new training information, and this will be used by the system to updates its internal rule set. The system does not simply memorize a particular sequence of postprocessing steps during a training session, but instead generalizes from the image data and from the actions of the human user so that new CT images can be refined appropriately. Experimental results have shown that IntelliPost improves the segmentation accuracy of the overall system by applying postprocessing rules. In tests two different CT datasets of hardwood logs, the use of IntelliPost resulted in improvements of 1.92% and 9.45%, respectively. For two different medical datasets, the use of IntelliPost resulted in improvements of 4.22% and 0.33%, respectively." @default.
• W2289009511 created "2016-06-24" @default.
• W2289009511 creator A5005921604 @default.
• W2289009511 creator A5065400092 @default.
• W2289009511 date "2004-01-01" @default.
• W2289009511 modified "2023-09-27" @default.
• W2289009511 title "Interactive machine learning for refinement and analysis of segmented ct/mri images" @default.
• W2289009511 cites W100169658 @default.
• W2289009511 cites W1269870073 @default.
• W2289009511 cites W1481844408 @default.
• W2289009511 cites W1484144136 @default.
• W2289009511 cites W1492324553 @default.
• W2289009511 cites W1498238238 @default.
• W2289009511 cites W149890774 @default.
• W2289009511 cites W1500551892 @default.
• W2289009511 cites W1502767928 @default.
• W2289009511 cites W1509640184 @default.
• W2289009511 cites W1515026043 @default.
• W2289009511 cites W1515620500 @default.
• W2289009511 cites W1515858175 @default.
• W2289009511 cites W1519788542 @default.
• W2289009511 cites W1521791417 @default.
• W2289009511 cites W1524761913 @default.
• W2289009511 cites W1548313863 @default.
• W2289009511 cites W1555800827 @default.
• W2289009511 cites W1561442812 @default.
• W2289009511 cites W1561445823 @default.
• W2289009511 cites W1564419782 @default.
• W2289009511 cites W1567143020 @default.
• W2289009511 cites W157077859 @default.
• W2289009511 cites W1573822799 @default.
• W2289009511 cites W1585743408 @default.
• W2289009511 cites W1594031697 @default.
• W2289009511 cites W1607340598 @default.
• W2289009511 cites W1622620102 @default.
• W2289009511 cites W1669494319 @default.
• W2289009511 cites W1688704361 @default.
• W2289009511 cites W1784695092 @default.
• W2289009511 cites W180736578 @default.
• W2289009511 cites W193921880 @default.
• W2289009511 cites W1964064379 @default.
• W2289009511 cites W1964646364 @default.
• W2289009511 cites W1966411054 @default.
• W2289009511 cites W1966992150 @default.
• W2289009511 cites W1967099248 @default.
• W2289009511 cites W1967156832 @default.
• W2289009511 cites W1968968976 @default.
• W2289009511 cites W1969417368 @default.
• W2289009511 cites W1970800786 @default.
• W2289009511 cites W1972544340 @default.
• W2289009511 cites W1975393892 @default.
• W2289009511 cites W1978396244 @default.
• W2289009511 cites W1979432452 @default.
• W2289009511 cites W1979622972 @default.
• W2289009511 cites W1979920698 @default.
• W2289009511 cites W1980826790 @default.
• W2289009511 cites W1991349032 @default.
• W2289009511 cites W1996066470 @default.
• W2289009511 cites W1996111510 @default.
• W2289009511 cites W2005676839 @default.
• W2289009511 cites W2010432086 @default.
• W2289009511 cites W2012896611 @default.
• W2289009511 cites W2014086378 @default.
• W2289009511 cites W2016396776 @default.
• W2289009511 cites W2020999234 @default.
• W2289009511 cites W2021511865 @default.
• W2289009511 cites W2023438527 @default.
• W2289009511 cites W2024168391 @default.
• W2289009511 cites W2026097151 @default.
• W2289009511 cites W2028460852 @default.
• W2289009511 cites W2029949252 @default.
• W2289009511 cites W2032427901 @default.
• W2289009511 cites W2033849769 @default.
• W2289009511 cites W2034539098 @default.
• W2289009511 cites W2034864592 @default.
• W2289009511 cites W2037420363 @default.
• W2289009511 cites W2037559018 @default.
• W2289009511 cites W2037718318 @default.
• W2289009511 cites W2038349403 @default.
• W2289009511 cites W2038584908 @default.
• W2289009511 cites W2040899664 @default.
• W2289009511 cites W2042243997 @default.
• W2289009511 cites W2049263856 @default.
• W2289009511 cites W2051084846 @default.
• W2289009511 cites W2051381803 @default.
• W2289009511 cites W2051754942 @default.
• W2289009511 cites W2058182745 @default.
• W2289009511 cites W2059264680 @default.
• W2289009511 cites W2059269831 @default.
• W2289009511 cites W2060591526 @default.
• W2289009511 cites W2067688310 @default.
• W2289009511 cites W2069610368 @default.
• W2289009511 cites W2071122929 @default.
• W2289009511 cites W2075690349 @default.
• W2289009511 cites W2083970667 @default.
• W2289009511 cites W2084995593 @default.
• W2289009511 cites W2086627000 @default.
• W2289009511 cites W2088059995 @default.
• W2289009511 cites W2091632190 @default.
• W2289009511 cites W2094242605 @default.

• next