Smart object counter
Counting people from surveillance videos, counting cells from microscopic images are very tedious and time-consuming work for human being. In this project, a software will be developed to localize and count the objects with similar characteristic in the image or video. We may assumed that the object...
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Nanyang Technological University
2023
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sg-ntu-dr.10356-1661282023-04-21T15:38:50Z Smart object counter Pong, Jeremy Zhi Jun Loke Yuan Ren School of Computer Science and Engineering yrloke@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Counting people from surveillance videos, counting cells from microscopic images are very tedious and time-consuming work for human being. In this project, a software will be developed to localize and count the objects with similar characteristic in the image or video. We may assumed that the object is known with some prior knowledge for machine learning. However, objects may have some variations from the image due to size, lighting, perspective view issue, overlapping issue etc. Bachelor of Science in Data Science and Artificial Intelligence 2023-04-18T13:55:43Z 2023-04-18T13:55:43Z 2023 Final Year Project (FYP) Pong, J. Z. J. (2023). Smart object counter. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/166128 https://hdl.handle.net/10356/166128 en SCSE22-0189 application/pdf Nanyang Technological University |
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Nanyang Technological University |
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Singapore Singapore |
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English |
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Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision |
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Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Pong, Jeremy Zhi Jun Smart object counter |
| description |
Counting people from surveillance videos, counting cells from microscopic images are very tedious and time-consuming work for human being. In this project, a software will be developed to localize and count the objects with similar characteristic in the image or video. We may assumed that the object is known with some prior knowledge for machine learning. However, objects may have some variations from the image due to size, lighting, perspective view issue, overlapping issue etc. |
| author2 |
Loke Yuan Ren |
| author_facet |
Loke Yuan Ren Pong, Jeremy Zhi Jun |
| format |
Final Year Project |
| author |
Pong, Jeremy Zhi Jun |
| author_sort |
Pong, Jeremy Zhi Jun |
| title |
Smart object counter |
| title_short |
Smart object counter |
| title_full |
Smart object counter |
| title_fullStr |
Smart object counter |
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Smart object counter |
| title_sort |
smart object counter |
| publisher |
Nanyang Technological University |
| publishDate |
2023 |
| url |
https://hdl.handle.net/10356/166128 |
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