Deep learning methods with less supervision
To tackle the immense burden of acquiring accurate, pixel-level annotations for semantic segmentation tasks, we propose a weakly-supervised deep learning framework. We incorporate state-of-the-art foundational models to propagate pseudo-labels. Then, explore the viability of training a fully convolu...
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Format: | Final Year Project |
Language: | English |
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Nanyang Technological University
2023
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Online Access: | https://hdl.handle.net/10356/172909 |
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Institution: | Nanyang Technological University |
Language: | English |
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