Semantic-Sensitive Classification for Large Image Library
With advances in multimedia technology, image data with various formats is is becoming available at an explosive rate from various domain applications. How to efficiently organise and access them has been an extremely important issue and enjoying growing attention. In this paper, we present results...
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| Main Authors: | , , |
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| Format: | text |
| Language: | English |
| Published: |
Institutional Knowledge at Singapore Management University
2005
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| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/sis_research/1236 http://doi.ieeecomputersociety.org/10.1109/MMMC.2005.66 |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | With advances in multimedia technology, image data with various formats is is becoming available at an explosive rate from various domain applications. How to efficiently organise and access them has been an extremely important issue and enjoying growing attention. In this paper, we present results from experimental studies investigating performance of image classification for a novel dimension reduction scheme with hybrid architecture. We demonstrate that not only can the method provide superior quality of classification accuracy with various machine learning based classifier but also substantially speed up training and categorisation process. Moreover, it is fairly robust against various kinds of visual distortions and noises. |
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