Deep learning model for doors detection: A contribution for context-awareness recognition of patients with Parkinson’s disease

作者：

Highlights：

• A real-time deep learning-based door detection model based on was presented.

• Based on transfer-learning concepts, it was used a pre-trained MobileNet-SSD.

• Computational method runs on portable device and uses a miniaturized camera.

• Spatiotemporal data through video sequences serve as input of the final DL model.

• Real-time testing highlights model efficiency and time-efficiency.

摘要

•A real-time deep learning-based door detection model based on was presented.•Based on transfer-learning concepts, it was used a pre-trained MobileNet-SSD.•Computational method runs on portable device and uses a miniaturized camera.•Spatiotemporal data through video sequences serve as input of the final DL model.•Real-time testing highlights model efficiency and time-efficiency.

论文关键词：Object detection,Deep-learning,RPi,Parkinson’s disease

论文评审过程：Received 8 July 2022, Revised 17 August 2022, Accepted 25 August 2022, Available online 30 August 2022, Version of Record 5 September 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.118712