Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/140456
Title: | Vision system development for hybrid robot-gripper to perform manipulation tasks in the food industry for object detection and localization | Authors: | Yao, Lingjie | Keywords: | Engineering::Mechanical engineering | Issue Date: | 2020 | Publisher: | Nanyang Technological University | Project: | C066 | Abstract: | 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. | URI: | https://hdl.handle.net/10356/140456 | Schools: | School of Mechanical and Aerospace Engineering | Research Centres: | Robotics Research Centre | Fulltext Permission: | restricted | Fulltext Availability: | With Fulltext |
Appears in Collections: | MAE Student Reports (FYP/IA/PA/PI) |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
NanyangTechnologicalUniversity_MAE_Final Year Report_Final Version_ProjectCode_C066_YAOLINGJIE.pdf Restricted Access | 4.16 MB | Adobe PDF | View/Open |
Page view(s)
387
Updated on Mar 28, 2024
Download(s) 50
32
Updated on Mar 28, 2024
Google ScholarTM
Check
Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.