Development Application for Identify Thai Banknote by Voice for Blindness via Smartphone - หงษ์บุญมี ณัฐวดี; แสงตาล กาญจนา (JOURNAL OF INFORMATION SCIENCE AND TECHNOLOGY, 2019)
The aim of this research is to develop an application to help identify Thai banknotes by voice for the blindness on the Smartphone android operating system. This research applied deep learning technique for image recognition and text to speech for Smartphone pronunciation. The process began with a collection of 2,700 images of Thai banknotes by analyzing and creating an image classification model using a Convolution Neural Network, using MobileNet algorithm through Tensorflow library. Then, the model was developed to be a Smartphone application. The application is developed with Android studio, JAVA language and Text to Speech​​ for pronunciation. The model performance test results obtained with an accuracy of 95.00%. The test of the application found that the banknote can be classified correctly 84.00%. The evaluation of user applications found that the average satisfaction was 4.33, the standard deviation 0.56, at a good level. It can conclude that this application makes it easier for the blindness to discover banknotes, because banknotes can identified by voice and are convenient for the blindness to use anywhere, anytime. It also helps to promote a lifestyle for the blindness so that they can live their basic life more conveniently.