Titlebook: Learning Classifier Systems; 11th International W Jaume Bacardit,Will Browne,Martin V. Butz Conference proceedings 2010 Springer Berlin Hei

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Ajay Kumar Tanwani,Muddassar Farooqes in imaging systems, image reconstruction, noise correctioThis volume addresses a wide range of issues in the field of nuclear medicine imaging, with an emphasis on the latest research findings. Initial chapters set the scene by considering the role of imaging in nuclear medicine from the medical

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Jose G. Moreno-Torres,Xavier Llorà,David E. Goldberg,Rohit Bhargavaew developments, such as imaging contrast agents and virtualThepastdecadehasseendramaticadvances inurologyandimaging. Thesechangesareevident in improvements in laparoscopic surgery as well as in the emergence of multidetector CT, with multiplanar reformatting and FDG-PET-CT as routine imaging method

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How Fitness Estimates Interact with Reproduction Rates: Towards Variable Offspring Set Sizes in XCSFnal, thus—dependent on the difficulty of the approximation problem—preventing further learning improvements. In order to speed-up learning where possible while still assuring learning success, we propose an adaptive offspring set size that may depend on the current reliability of classifier paramete

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Jose G. Moreno-Torres,Xavier Llorà,David E. Goldberg,Rohit Bhargavaus books have focused on the more common urologic tumors such as bladder, prostate, andkidneycancer,nonehasattemptedacomprehensivereviewofthestateoftheartofimaging in most of the tumors involved in urologic onc978-1-4471-6083-0978-1-84628-759-6

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