Significance of physical factors on activities of daily living in patients with tetraplegia after spinal cord injury: a retrospective study.

Background: Tetraplegia is a debilitating sequela of spinal cord injury (SCI). However, comprehensive approaches for determining the influence of various factors on activities of daily living (ADL) in patients with tetraplegia are limited. Therefore, this study aimed to determine the influence of physical factors on ADL in patients with tetraplegia after adjusting for demographic, SCI-related, and cognitive factors.

Occluded Pedestrian-Attribute Recognition for Video Sensors Using Group Sparsity.

Pedestrians are often obstructed by other objects or people in real-world vision sensors. These obstacles make pedestrian-attribute recognition (PAR) difficult; hence, occlusion processing for visual sensing is a key issue in PAR. To address this problem, we first formulate the identification of non-occluded frames as temporal attention based on the sparsity of a crowded video.

Action-Driven Visual Object Tracking With Deep Reinforcement Learning.

In this paper, we propose an efficient visual tracker, which directly captures a bounding box containing the target object in a video by means of sequential actions learned using deep neural networks. The proposed deep neural network to control tracking actions is pretrained using various training video sequences and fine-tuned during actual tracking for online adaptation to a change of target and background. The pretraining is done by utilizing deep reinforcement learning (RL) as well as supervised learning.