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Application of Multimodal Deep Learning in Traffic Accident Severity Prediction: The Journey of F1 Score Improvement from 81% to 96%

This article deeply analyzes a multimodal deep learning project that improves the F1 score for traffic accident severity prediction from 81% to 96% by fusing tabular data and accident scene images. It covers technical architecture, model design, loss function optimization, and practical application value.

多模态学习深度学习交通事故预测ResNetFocal Loss计算机视觉机器学习数据融合智能交通应急响应

Published 2026-05-12 05:43Recent activity 2026-05-12 05:50Estimated read 1 min

Section 01

导读 / 主楼：Application of Multimodal Deep Learning in Traffic Accident Severity Prediction: The Journey of F1 Score Improvement from 81% to 96%

Introduction / Main Floor: Application of Multimodal Deep Learning in Traffic Accident Severity Prediction: The Journey of F1 Score Improvement from 81% to 96%

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