Vision system development for hybrid robot-gripper to perform manipulation tasks in the food industry for object detection and localization

In this paper, it introduced how to apply and set up the computer vision system for the food packaging production line, in which this computer vision system based on the deep learning algorithm to develop. The paper had introduced and compared three of the current famous deep learning frameworks, wh...

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Main Author: Yao, Lingjie
Other Authors: Chen I-Ming
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2020
Subjects:
Online Access:https://hdl.handle.net/10356/140456
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1404562023-03-04T20:00:46Z Vision system development for hybrid robot-gripper to perform manipulation tasks in the food industry for object detection and localization Yao, Lingjie Chen I-Ming School of Mechanical and Aerospace Engineering Robotics Research Centre michen@ntu.edu.sg Engineering::Mechanical engineering In this paper, it introduced how to apply and set up the computer vision system for the food packaging production line, in which this computer vision system based on the deep learning algorithm to develop. The paper had introduced and compared three of the current famous deep learning frameworks, which are TensorFlow, PyTorch, and Darknet. At the same time, it introduced and compared two of the different deep learning algorithms, which are the You Only Look Once (YOLO) and the Single Shot MultiBox Detector (SSD). Besides, the paper had demonstrated how to reproduce the YOLO and SSD model training procedures based on the PyTorch framework. In addition, the report demonstrated and discussed their actual object detecting results. Bachelor of Engineering (Mechanical Engineering) 2020-05-29T05:07:13Z 2020-05-29T05:07:13Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/140456 en C066 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Mechanical engineering
spellingShingle Engineering::Mechanical engineering
Yao, Lingjie
Vision system development for hybrid robot-gripper to perform manipulation tasks in the food industry for object detection and localization
description In this paper, it introduced how to apply and set up the computer vision system for the food packaging production line, in which this computer vision system based on the deep learning algorithm to develop. The paper had introduced and compared three of the current famous deep learning frameworks, which are TensorFlow, PyTorch, and Darknet. At the same time, it introduced and compared two of the different deep learning algorithms, which are the You Only Look Once (YOLO) and the Single Shot MultiBox Detector (SSD). Besides, the paper had demonstrated how to reproduce the YOLO and SSD model training procedures based on the PyTorch framework. In addition, the report demonstrated and discussed their actual object detecting results.
author2 Chen I-Ming
author_facet Chen I-Ming
Yao, Lingjie
format Final Year Project
author Yao, Lingjie
author_sort Yao, Lingjie
title Vision system development for hybrid robot-gripper to perform manipulation tasks in the food industry for object detection and localization
title_short Vision system development for hybrid robot-gripper to perform manipulation tasks in the food industry for object detection and localization
title_full Vision system development for hybrid robot-gripper to perform manipulation tasks in the food industry for object detection and localization
title_fullStr Vision system development for hybrid robot-gripper to perform manipulation tasks in the food industry for object detection and localization
title_full_unstemmed Vision system development for hybrid robot-gripper to perform manipulation tasks in the food industry for object detection and localization
title_sort vision system development for hybrid robot-gripper to perform manipulation tasks in the food industry for object detection and localization
publisher Nanyang Technological University
publishDate 2020
url https://hdl.handle.net/10356/140456
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