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Question 141/192
Consider the following scenario: You are building a multimodal system for autonomous driving that uses both camera images and LiDAR data to perceive the environment. The LiDAR data is sparse and noisy, while the camera images are rich in visual details but can be affected by lighting conditions. Which of the following fusion strategies is MOST robust and effective for combining these two modalities?
Correct Answer: C
Early fusion allows the model to learn complex relationships between the two modalities, leveraging the strengths of each modality while mitigating their weaknesses. Raw data fusion can be difficult to train. Late fusion might miss important cross-modal interactions. Discarding either modality reduces the information available to the system. Camera images are important even though they might be affected by lighting conditions.
- Question List (192q)
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