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Implementation of Image Semantic Segmentation on Android Device using Deep Learning  

Lee, Yong-Hwan (Dept. of Digital Contents, Institute of Convergence and Creativity, Wonkwang University)
Kim, Youngseop (Dept. of Electronics and Electrical Engineering, Dankook University)
Publication Information
Journal of the Semiconductor & Display Technology / v.19, no.2, 2020 , pp. 88-91 More about this Journal
Abstract
Image segmentation is the task of partitioning an image into multiple sets of pixels based on some characteristics. The objective is to simplify the image into a representation that is more meaningful and easier to analyze. In this paper, we apply deep-learning to pre-train the learning model, and implement an algorithm that performs image segmentation in real time by extracting frames for the stream input from the Android device. Based on the open source of DeepLab-v3+ implemented in Tensorflow, some convolution filters are modified to improve real-time operation on the Android platform.
Keywords
Image Segmentation; Semantic Segmentation; Object Detection; Deep Learning; Tensorflow;
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