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Related Questions
- How do large language models perform in low-light environments compared to traditional computer vision models?
- What are the common challenges faced by large language models in detecting objects in low-light conditions?
- Can large language models be trained to adapt to low-light environments, and if so, what techniques are used?
- How does the performance of large language models degrade in low-light environments, and what are the key factors contributing to this degradation?
- Are there any specific architectures or techniques that can improve the performance of large language models in low-light object detection?
- Can large language models be combined with other computer vision techniques, such as image enhancement or super-resolution, to improve performance in low-light environments?
- What are the potential applications of large language models in low-light object detection, such as surveillance or autonomous vehicles?
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