Machine learning: model compression techniques and deployment on Android platform

Machine learning: model compression techniques and deployment on Android platform

As Artificial Intelligence (AI) industry grows rapidly in recent years, many applications of deep learning are applied in mobile devices where resources are limited. Therefore, model compression and acceleration techniques are of great importance for achieving real-time requirements. In this study,...

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Bibliographic Details
Main Author: Jin, Chengkai
Other Authors: Jun Zhao
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2022
Subjects:
Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Online Access:https://hdl.handle.net/10356/156646
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Institution: Nanyang Technological University
Language: English
Description
Summary:As Artificial Intelligence (AI) industry grows rapidly in recent years, many applications of deep learning are applied in mobile devices where resources are limited. Therefore, model compression and acceleration techniques are of great importance for achieving real-time requirements. In this study, several classic model compression techniques are discussed and compared by their performance on image recognition task. Additionally, an Android application able to classify images is built.

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