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"MSD-NAS: multi-scale dense neural architecture search for real-time pe" by Sui Paul Ang, Son Lam Phung et al.

Accurate detection of pedestrian lanes is a crucial criterion for vision-impaired people to navigate freely and safely. The current deep learning methods have achieved reasonable accuracy at this task. However, they lack practicality for real-time pedestrian lane detection due to non-optimal accuracy, speed, and model size trade-off. Hence, an optimized deep neural network (DNN) for pedestrian lane detection is required. Designing a DNN from scratch is a laborious task that requires significant ...
Short Term Visual Memory Assistive Navigation Deep Learning Neural Architecture Search Edestrian Lane Detection Eal Time Video Processing
Source: uow.edu.au

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