Implementation of Machine Learning in Android Applications
Widad, Ramiz (2024)
2024
All rights reserved. This publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited.
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2024052515749
https://urn.fi/URN:NBN:fi:amk-2024052515749
Tiivistelmä
The objective of this thesis was to summarize the core concepts of machine learning and delve into TensorFlow Lite, a leading on-device machine learning framework, with a particular focus on its application within the Android platform.
Consequently, a native Android mobile application was developed to incorporate machine learning object detection functionalities. The application leveraged a pre-trained model provided by TensorFlow that was specifically created for object detection tasks. The application was successfully able to detect objects with high accuracy and responsiveness, providing real-time inference capabilities.
Consequently, a native Android mobile application was developed to incorporate machine learning object detection functionalities. The application leveraged a pre-trained model provided by TensorFlow that was specifically created for object detection tasks. The application was successfully able to detect objects with high accuracy and responsiveness, providing real-time inference capabilities.