Konversi Ui Prototype Android Ke Xml Code Dengan Tensorflow Object Detection Api Sebagai Detector Objek
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Institusion
Politeknik Negeri Jember
Author
Pratama, Vyan Ary
Subject
458 - Teknik Informatika
Datestamp
2022-01-05 03:13:20
Abstract :
Prototype design is a very important part when creating an application. Design prototyping is done by a designer and designing by a developer to implement the design that has been made into a code structure. The implementation of a prototype design takes a long time to process and results in the process of making an application seem long just for designing. One solution to this problem is to use machine learning. However, due to the large variety of data from a prototype design, it is not enough to just use machine learning to classify parts of a prototype design such as buttons, icons, text input, radio buttons, check boxes, etc. Therefore we need to use deep learning. Basically, deep learning adapts a neural network algorithm with more layers. In this study, adding a User Interface (UI) design dataset such as buttons, icons, layouts, text input, radio buttons, check boxes, toggle buttons, labels. For example, the button has various variations and by using the Faster R-CNN method to detect objects - these objects are expected to increase the accuracy of previous studies. Key words : Machine Learning, Deep Learning, Android
Prototype design is a very important part when creating an application. Design prototyping is done by a designer and designing by a developer to implement the design that has been made into a code structure. The implementation of a prototype design takes a long time to process and results in the process of making an application seem long just for designing. One solution to this problem is to use machine learning. However, due to the large variety of data from a prototype design, it is not enough to just use machine learning to classify parts of a prototype design such as buttons, icons, text input, radio buttons, check boxes, etc. Therefore we need to use deep learning. Basically, deep learning adapts a neural network algorithm with more layers. In this study, adding a User Interface (UI) design dataset such as buttons, icons, layouts, text input, radio buttons, check boxes, toggle buttons, labels. For example, the button has various variations and by using the Faster R-CNN method to detect objects - these objects are expected to increase the accuracy of previous studies. Key words : Machine Learning, Deep Learning, Android
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