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Formula selection for intraocular power calculation using support vector machines and self-organizing maps.

, , , , , and . SMC, page 1111-1116. IEEE, (2011)

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On Selection of Intraocular Power Formula Using Support Vector Machines and Genetic Algorithm., , , , , and . ISMVL, page 65-70. IEEE Computer Society, (2013)A Two-Pronged Approach of Power-Aware Voltage Scheduling for Real-Time Task Graphs in Multi-processor Systems., , , and . ISMVL, page 151-156. IEEE Computer Society, (2009)Classification of Interview Sheets Using Self-Organizing Maps for Determination of Ophthalmic Examinations., , , , and . ICONIP (4), volume 7666 of Lecture Notes in Computer Science, page 148-155. Springer, (2012)On Waiting-time Estimation for Outpatients at Department of Ophthalmology., , , , and . ICETET, page 24-29. IEEE, (2012)Detection of tumors on stomach wall in X-ray images., , , , , , , and . FUZZ-IEEE, page 1-5. IEEE, (2010)On selection of intraocular power formula based on data classification using self-organizing maps., , , , , and . SMC, page 1147-1152. IEEE, (2010)On Determination of Ophthalmic Examinations Using Support Vector Machines., , , , , and . SMC, page 3402-3407. IEEE, (2013)Stochastic visualization of intersection curves of implicit surfaces., , , , , , , and . Comput. Graph., 31 (2): 230-242 (2007)Application and performance evaluation of a method using block structures for saddle point problems appearing in image reconstruction problems., , and . JSIAM Lett., (2022)Video object segmentation using color-component-selectable learning for self-organizing maps., , , , and . Artif. Life Robotics, 16 (2): 258-261 (2011)