Robustness of Deep Learning Methods for Occluded Object Detection - A Study Introducing a Novel Occlusion Dataset

Wu, Ziling; Moemeni, Armaghan; Caleb-Solly, Praminda; Castle-Green, Simon

doi:10.1109/ijcnn54540.2023.10191368

All Outputs (2)

TAS for Cats: An Artist-led Exploration of Trustworthy Autonomous Systems for Companion Animals (2023)
Conference Proceeding

Cat Royale is an artist-led exploration of trustworthy autonomous systems (TAS) created by the TAS Hub's creative ambassadors Blast Theory. A small community of cats inhabits a purpose built 'cat utopia' at the centre of which a robot arm tries to en... Read More about TAS for Cats: An Artist-led Exploration of Trustworthy Autonomous Systems for Companion Animals.

Robustness of Deep Learning Methods for Occluded Object Detection - A Study Introducing a Novel Occlusion Dataset (2023)
Conference Proceeding

A large number of deep learning based object detection algorithms have been proposed and applied in a wide range of domains such as security, autonomous driving and robotics. In practical usage, objects being occluded are common, and can result in re... Read More about Robustness of Deep Learning Methods for Occluded Object Detection - A Study Introducing a Novel Occlusion Dataset.