Driver distraction detection using single convolutional neural network
| Autor: | Hyun-Kyun Choi, Whui Kim, Byung-Tae Jang, Jinsu Lim |
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| Rok vydání: | 2017 |
| Předmět: |
Focus (computing)
Computer science Speech recognition Distraction 0202 electrical engineering electronic engineering information engineering 020206 networking & telecommunications 020201 artificial intelligence & image processing 02 engineering and technology Convolutional neural network Residual neural network Task (project management) |
| Zdroj: | ICTC |
| Popis: | Driver status detection is an essential task because driver distraction, fatigue, and drowsiness of driver are serious causes of traffic accident in recent. In this paper, we focus on driver distraction and propose a method to detect driver distraction. We detect driver distraction using single Convolutional Neural Network model such as Inception ResNet and MobileNet. As our experiments, both models can be trained with a small amount of dataset and checkpoints which were pre-trained with ILSVRC2012 dataset. Furthermore, although our training dataset consists images of two subjects, our method shows reliable result for other subjects. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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