Matches in SemOpenAlex for { <https://semopenalex.org/work/W2099407712> ?p ?o ?g. }
Showing items 1 to 85 of
85
with 100 items per page.
- W2099407712 abstract "Feature selection is of great importance in recognition system design because it directly affects the overall performance of the recognition system. Feature selection can be considered as a problem of global combinatorial optimization. It is a very time-consuming task to search the most suitable features amongst a huge number of possible feature combinations, therefore, an effective and efficient search technique is desired. In this paper, we use genetic algorithms (GA) to design a feature selection approach for handwritten Chinese character recognition. Four contributions are claimed: First, the general transformed divergence among classes, which is derived from Mahalanobis distances, is proposed to be the fitness function in the feature selection based on GA; Second, a special crossover operator other than traditional one is given; Third, a special criterion of terminating selections is inferred from the criterion of minimum error probability in a Bayes classifier; Fourth, we compare our method with the feature selection based on branch-and-bound algorithm (BAB), which is often used to reduce the calculation of feature selection via exhaustive search. The analyses of the experimental results can be proceeded that traditional GA is an ergodic Markov chain, while, BAB is a depth first heuristic algorithm for exhaustive search. We conclude that the GA-based method proposed in this paper is promising to solve the feature selection problems in a multidimensional space." @default.
- W2099407712 created "2016-06-24" @default.
- W2099407712 creator A5026471954 @default.
- W2099407712 creator A5057722627 @default.
- W2099407712 creator A5059246379 @default.
- W2099407712 date "2002-11-27" @default.
- W2099407712 modified "2023-09-25" @default.
- W2099407712 title "Feature selection for handwritten Chinese character recognition based on genetic algorithms" @default.
- W2099407712 cites W1967093065 @default.
- W2099407712 cites W1991100763 @default.
- W2099407712 cites W2103537992 @default.
- W2099407712 cites W2107951961 @default.
- W2099407712 doi "https://doi.org/10.1109/icsmc.1998.727504" @default.
- W2099407712 hasPublicationYear "2002" @default.
- W2099407712 type Work @default.
- W2099407712 sameAs 2099407712 @default.
- W2099407712 citedByCount "17" @default.
- W2099407712 countsByYear W20994077122012 @default.
- W2099407712 crossrefType "proceedings-article" @default.
- W2099407712 hasAuthorship W2099407712A5026471954 @default.
- W2099407712 hasAuthorship W2099407712A5057722627 @default.
- W2099407712 hasAuthorship W2099407712A5059246379 @default.
- W2099407712 hasConcept C106284839 @default.
- W2099407712 hasConcept C11413529 @default.
- W2099407712 hasConcept C119857082 @default.
- W2099407712 hasConcept C122507166 @default.
- W2099407712 hasConcept C138885662 @default.
- W2099407712 hasConcept C148483581 @default.
- W2099407712 hasConcept C153180895 @default.
- W2099407712 hasConcept C154945302 @default.
- W2099407712 hasConcept C173801870 @default.
- W2099407712 hasConcept C176066374 @default.
- W2099407712 hasConcept C2776401178 @default.
- W2099407712 hasConcept C41008148 @default.
- W2099407712 hasConcept C41895202 @default.
- W2099407712 hasConcept C70518039 @default.
- W2099407712 hasConcept C81917197 @default.
- W2099407712 hasConcept C83665646 @default.
- W2099407712 hasConcept C8880873 @default.
- W2099407712 hasConcept C95623464 @default.
- W2099407712 hasConceptScore W2099407712C106284839 @default.
- W2099407712 hasConceptScore W2099407712C11413529 @default.
- W2099407712 hasConceptScore W2099407712C119857082 @default.
- W2099407712 hasConceptScore W2099407712C122507166 @default.
- W2099407712 hasConceptScore W2099407712C138885662 @default.
- W2099407712 hasConceptScore W2099407712C148483581 @default.
- W2099407712 hasConceptScore W2099407712C153180895 @default.
- W2099407712 hasConceptScore W2099407712C154945302 @default.
- W2099407712 hasConceptScore W2099407712C173801870 @default.
- W2099407712 hasConceptScore W2099407712C176066374 @default.
- W2099407712 hasConceptScore W2099407712C2776401178 @default.
- W2099407712 hasConceptScore W2099407712C41008148 @default.
- W2099407712 hasConceptScore W2099407712C41895202 @default.
- W2099407712 hasConceptScore W2099407712C70518039 @default.
- W2099407712 hasConceptScore W2099407712C81917197 @default.
- W2099407712 hasConceptScore W2099407712C83665646 @default.
- W2099407712 hasConceptScore W2099407712C8880873 @default.
- W2099407712 hasConceptScore W2099407712C95623464 @default.
- W2099407712 hasLocation W20994077121 @default.
- W2099407712 hasOpenAccess W2099407712 @default.
- W2099407712 hasPrimaryLocation W20994077121 @default.
- W2099407712 hasRelatedWork W101306436 @default.
- W2099407712 hasRelatedWork W1551115843 @default.
- W2099407712 hasRelatedWork W1988277081 @default.
- W2099407712 hasRelatedWork W2024529640 @default.
- W2099407712 hasRelatedWork W2027709829 @default.
- W2099407712 hasRelatedWork W2050698510 @default.
- W2099407712 hasRelatedWork W2082395509 @default.
- W2099407712 hasRelatedWork W2084154192 @default.
- W2099407712 hasRelatedWork W2096375611 @default.
- W2099407712 hasRelatedWork W2132935827 @default.
- W2099407712 hasRelatedWork W2145139008 @default.
- W2099407712 hasRelatedWork W2167898728 @default.
- W2099407712 hasRelatedWork W2241909861 @default.
- W2099407712 hasRelatedWork W2286602577 @default.
- W2099407712 hasRelatedWork W2349904311 @default.
- W2099407712 hasRelatedWork W2368654489 @default.
- W2099407712 hasRelatedWork W2375921464 @default.
- W2099407712 hasRelatedWork W2386195695 @default.
- W2099407712 hasRelatedWork W2390171013 @default.
- W2099407712 hasRelatedWork W66488064 @default.
- W2099407712 isParatext "false" @default.
- W2099407712 isRetracted "false" @default.
- W2099407712 magId "2099407712" @default.
- W2099407712 workType "article" @default.