Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/158187
Title: Electrical component classification using 2D and 3D semantic segmentation
Authors: Zhou, Tongfang
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2022
Publisher: Nanyang Technological University
Source: 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
Project: B3091-211
Abstract: 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.
URI: https://hdl.handle.net/10356/158187
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

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