Journal of Physics Conference Series · 2018 · 10 citations · 4 references
ComputingComputer ScienceEducational TechnologyComputer VisionLanguage AcquisitionMachine LearningDeep LearningImage ProcessingLetter RecognitionNeural NetworksPattern RecognitionTransfer LearningConvolutional Neural NetworksDeep Learning-based ClassificationHandwriting Letter RecognitionHandwriting RecognitionHandwritten Character RecognitionKorean CultureNeural Network-based Recognition
Currently, popularity of Korean culture attracts many people to learn everything about Korea, particularly its language. To acquire Korean Language, every single learner needs to be able to understand Korean non-Latin character. A digital approach needs to be carried out in order to make Korean learning process easier. This study is done by using Deep Convolutional Neural Network (DCNN). DCNN performs the recognition process on the image based on the model that has been trained such as Inception-v3 Model. Subsequently, re-training process using transfer learning technique with the trained and re-trained value of model is carried though in order to develop a new model with a better performance without any specific systemic errors. The testing accuracy of this research results in 86,9%.
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