Electrical component classification using 2D and 3D semantic segmentation
Description: The student will focus on 2D/3D semantic segmentation on various semiconductor component, such as TSV, logic bump, memory bump etc. The objective is to detect defects in the buried interconnects inside the chip by detecting and identifying the above structures. It involves 2D/3D data pr...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2022
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| Online Access: | https://hdl.handle.net/10356/158187 |
| _version_ | 1826122331365310464 |
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| author | Zhou, Tongfang |
| author2 | Jiang Xudong |
| author_facet | Jiang Xudong Zhou, Tongfang |
| author_sort | Zhou, Tongfang |
| collection | NTU |
| description | Description: The student will focus on 2D/3D semantic segmentation on various semiconductor component, such as TSV, logic bump, memory bump etc. The objective is to detect defects in the buried interconnects inside the chip by detecting and identifying the above structures. It involves 2D/3D data processing for deep learning algorithm in object detection and segmentation. The student is expected to take an active role in understanding and preprocessing the data and learning relevant deep learning networks. The student is also expected to implement 3D data augmentation and train the 3D semantic segmentation individually. |
| first_indexed | 2024-10-01T05:46:27Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/158187 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:46:27Z |
| publishDate | 2022 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1581872023-07-07T19:08:03Z Electrical component classification using 2D and 3D semantic segmentation Zhou, Tongfang Jiang Xudong School of Electrical and Electronic Engineering Ramanpreet Singh Pahwa EXDJiang@ntu.edu.sg Engineering::Electrical and electronic engineering Description: The student will focus on 2D/3D semantic segmentation on various semiconductor component, such as TSV, logic bump, memory bump etc. The objective is to detect defects in the buried interconnects inside the chip by detecting and identifying the above structures. It involves 2D/3D data processing for deep learning algorithm in object detection and segmentation. The student is expected to take an active role in understanding and preprocessing the data and learning relevant deep learning networks. The student is also expected to implement 3D data augmentation and train the 3D semantic segmentation individually. Bachelor of Engineering (Electrical and Electronic Engineering) 2022-05-31T08:41:30Z 2022-05-31T08:41:30Z 2022 Final Year Project (FYP) Zhou, T. (2022). Electrical component classification using 2D and 3D semantic segmentation. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/158187 https://hdl.handle.net/10356/158187 en B3091-211 application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Electrical and electronic engineering Zhou, Tongfang Electrical component classification using 2D and 3D semantic segmentation |
| title | Electrical component classification using 2D and 3D semantic segmentation |
| title_full | Electrical component classification using 2D and 3D semantic segmentation |
| title_fullStr | Electrical component classification using 2D and 3D semantic segmentation |
| title_full_unstemmed | Electrical component classification using 2D and 3D semantic segmentation |
| title_short | Electrical component classification using 2D and 3D semantic segmentation |
| title_sort | electrical component classification using 2d and 3d semantic segmentation |
| topic | Engineering::Electrical and electronic engineering |
| url | https://hdl.handle.net/10356/158187 |
| work_keys_str_mv | AT zhoutongfang electricalcomponentclassificationusing2dand3dsemanticsegmentation |