Show simple item record

dc.contributor.authorLau, Mian Mian
dc.contributor.supervisorZhuquan Zangen_US
dc.contributor.supervisorHann Limen_US

A new convolutional deep feedforward network (C-DFN) is proposed to detect vulnerable road users at 57.9% misclassification rate using Caltech Dataset. Instead of going deeper, three C-DFN is stacked to achieve 43.4% misclassification rate. Part-based C-DFN further reduces the rate of 42.5% to tackle occlusion problem. In addition, investigation of adaptive activation functions are performed to understand the effect of saturated and non-saturated functions in mitigating the vanishing and exploding gradient issues of neural networks.

dc.publisherCurtin Universityen_US
dc.titleVulnerable Road Users Detection using Convolutional Deep Feedforward Networken_US
curtin.departmentCurtin Malaysiaen_US
curtin.accessStatusOpen accessen_US
curtin.facultyCurtin Malaysiaen_US
curtin.contributor.orcidLau, Mian Mian [0000-0002-8940-0347]en_US

Files in this item


This item appears in the following Collection(s)

Show simple item record