KNOWLEDGE DISTILLATION AND SIAMESE NETWORK ADOPTION FOR SEMANTIC SEGMENTATION USING SEMI- SUPERVISED LEARNING
The demand for large amounts of labeled data and large computations is a common problem in semantic segmentation. Semi-supervised answers the problem by utilizing data without labels in the training process, but choosing the right method in the unsupervised learning process is a challenge in itself....
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| 格式: | Theses |
| 語言: | Indonesia |
| 在線閱讀: | https://digilib.itb.ac.id/gdl/view/69104 |
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| 機構: | Institut Teknologi Bandung |
| 語言: | Indonesia |