影像辨識論文:Drive-Net: Convolutional Network for Driver Distraction Detection

Image for post
Image for post

介紹:

本文提出了一個名為Drive-Net的神經網路,用來偵測駕駛在開車時的各種分心行為。

方法:結合了CNN和random forest的一個Neural Network

作者在CNN (U-Net based去修改)的Fully Connected層後,Output到Random Forest進行final class label的prediction

class labelc0: safe driving
c1: texting (right hand)
c2: talking on the phone (right hand)
c3: texting (left hand)
c4: talking on the phone (left hand)
c5: operating the radio
c6: drinking
c7: reaching behind
c8: hair and makeup
c9: talking to passenger

疑點:

作者雖然有和其他的演算法架構去做Benchmark,可是對象都是一些比較傳統的演算法MLP、RNN、VGG16,而不是最近幾年火紅的ResNet、Inception Net……等。可能是為了要讓自己的結果看起來不錯,這就不得而知了。整體來說,該論文相當的精簡,只用了4頁就寫完,是屬於Image Classification的論文。

論文:

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