Optimizing Large Railway Vision Models for Efficient In-Context Learning
Large railway vision models (LRVMs) have exhibited remarkable performance in tackling diverse railway-related vision-based tasks, attributed to their capacity for in-context learning (ICL). However, in terms of speed and memory usage, these models suffer from inefficient hardware utilization, partic...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10975287/ |
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