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Driver Drowsiness Detection
基於ViT架構的駕駛員疲勞檢測模型，在UTA RLDD數據集上微調，準確率達97.5%
Downloads 131
Release Time : 4/3/2023
Model Overview
該模型是基於Google的ViT-base-patch16-224-in21k模型微調而成，專門用於駕駛員疲勞狀態檢測。通過分析面部圖像，可準確識別駕駛員是否處於疲勞狀態。
Model Features
高準確率
在評估集上達到97.5%的準確率，表現優異
基於ViT架構
採用先進的Vision Transformer架構，能有效捕捉圖像全局特徵
小樣本微調
基於預訓練模型微調，只需相對少量訓練數據即可獲得良好效果
Model Capabilities
駕駛員疲勞狀態識別
面部圖像分類
即時監控分析
Use Cases
交通安全
車載疲勞預警系統
集成到車載系統中即時監測駕駛員狀態
可有效降低因疲勞駕駛導致的事故風險
運輸車隊管理
監控長途運輸司機疲勞狀態
提高車隊安全管理水平
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