Enhanced self-organising map model for surface reconstruction of unstructured data
Surface reconstruction (SR) is a process of recovering the digital representation of an object in reverse engineering. When the unstructured data are applied in the SR process, incorrect surface is produced because the data do not have any connectivity information. Self-Organising Map (SOM) models w...
保存先:
第一著者: | You, Cheng Chun |
---|---|
フォーマット: | Final Year Project / Dissertation / Thesis |
出版事項: |
2023
|
主題: | |
オンライン・アクセス: | http://eprints.utar.edu.my/6252/1/CEA_2023_YCC.pdf http://eprints.utar.edu.my/6252/ |
タグ: |
タグ追加
タグなし, このレコードへの初めてのタグを付けませんか!
|
類似資料
-
Multiple 2D self organising map network for surface reconstruction of 3D unstructured data
著者:: Lim, Seng Poh
出版事項: (2015) -
Pre-processing and classification of airborne hyperspectral data for wetlands mapping
著者:: Lau, Alvin Meng Shin
出版事項: (2004) -
Examining the least square method to retrieve sea surface salinity from MODIS satellite data
著者:: Marghany, Maged
出版事項: (2010) -
Kohonen-swarm algorithm for unstructured data in surface reconstruction
著者:: Forkan, Fadni, 等
出版事項: (2008) -
Enhanced air quality index prediction using a hybrid convolutional network
著者:: Pei-Chun Lin, Pei-Chun Lin, 等
出版事項: (2024)