Enhanced Symbol Recognition Based on Data Augmentation in Engineering Drawings
Recognizing symbols has received research interest for image analytics of engineering diagrams recently to improve identification and retrieval of specific symbols. Convolutional Neural Network (CNN) have become a more popular approach for symbol recognition compared to structural, syntactic, and st...
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis |
| Language: | English |
| Published: |
2023
|
| Subjects: | |
| Online Access: | http://utpedia.utp.edu.my/id/eprint/24858/1/Ong%20Kai%20Bin_19001721.pdf http://utpedia.utp.edu.my/id/eprint/24858/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| id |
oai:utpedia.utp.edu.my:24858 |
|---|---|
| record_format |
eprints |
| spelling |
oai:utpedia.utp.edu.my:248582023-09-14T07:08:05Z http://utpedia.utp.edu.my/id/eprint/24858/ Enhanced Symbol Recognition Based on Data Augmentation in Engineering Drawings ONG, KAI BIN T Technology (General) Recognizing symbols has received research interest for image analytics of engineering diagrams recently to improve identification and retrieval of specific symbols. Convolutional Neural Network (CNN) have become a more popular approach for symbol recognition compared to structural, syntactic, and statistical techniques 2023-09 Thesis NonPeerReviewed text en http://utpedia.utp.edu.my/id/eprint/24858/1/Ong%20Kai%20Bin_19001721.pdf ONG, KAI BIN (2023) Enhanced Symbol Recognition Based on Data Augmentation in Engineering Drawings. Masters thesis, Universiti Teknologi PETRONAS. |
| institution |
Universiti Teknologi Petronas |
| building |
UTP Resource Centre |
| collection |
Institutional Repository |
| continent |
Asia |
| country |
Malaysia |
| content_provider |
Universiti Teknologi Petronas |
| content_source |
UTP Electronic and Digitized Intellectual Asset |
| url_provider |
http://utpedia.utp.edu.my/ |
| language |
English |
| topic |
T Technology (General) |
| spellingShingle |
T Technology (General) ONG, KAI BIN Enhanced Symbol Recognition Based on Data Augmentation in Engineering Drawings |
| description |
Recognizing symbols has received research interest for image analytics of engineering diagrams recently to improve identification and retrieval of specific symbols. Convolutional Neural Network (CNN) have become a more popular approach for symbol recognition compared to structural, syntactic, and statistical techniques |
| format |
Thesis |
| author |
ONG, KAI BIN |
| author_facet |
ONG, KAI BIN |
| author_sort |
ONG, KAI BIN |
| title |
Enhanced Symbol Recognition Based on Data Augmentation in
Engineering Drawings |
| title_short |
Enhanced Symbol Recognition Based on Data Augmentation in
Engineering Drawings |
| title_full |
Enhanced Symbol Recognition Based on Data Augmentation in
Engineering Drawings |
| title_fullStr |
Enhanced Symbol Recognition Based on Data Augmentation in
Engineering Drawings |
| title_full_unstemmed |
Enhanced Symbol Recognition Based on Data Augmentation in
Engineering Drawings |
| title_sort |
enhanced symbol recognition based on data augmentation in
engineering drawings |
| publishDate |
2023 |
| url |
http://utpedia.utp.edu.my/id/eprint/24858/1/Ong%20Kai%20Bin_19001721.pdf http://utpedia.utp.edu.my/id/eprint/24858/ |
| _version_ |
1778164441467060224 |
| score |
13.214268 |