Adaptation of object detection networks under anomalous conditions
Out of distribution (OOD) samples can negatively affect the performance of deep neural networks. When deep neural networks are used in cyber-physical systems, it may be vulnerable to OOD data, leading to large errors and compromise the safety of the system. This paper proposes combining OOD explanat...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2023
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| Online Access: | https://hdl.handle.net/10356/166069 |