Complete Scene Parsing for Autonomous Navigation in Unstructured Environments

dc.contributor.authorRout, Bijay Kumar
dc.date.accessioned2023-09-04T10:24:11Z
dc.date.available2023-09-04T10:24:11Z
dc.date.issued2020
dc.description.abstractRecent developments in Machine Learning and Computer Vision have enabled progress in autonomous navigation. However, most of the existing research focuses on European driving situations, with not much progress made in the Indian context. Our paper aims to achieve complete spatial understanding for the Indian context. Our focus is directed towards Semantic Segmentation and Instance Segmentation. We aim to develop an autonomous navigation pipeline by a combination of both approaches. Using DeepLabv3+ for Semantic Segmentation we achieve an mIOU of 68.58%, and using Hybrid Task Cascade we achieve an Average Recall of 56.5%.en_US
dc.identifier.urihttps://ieeexplore.ieee.org/abstract/document/9081829
dc.identifier.urihttp://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/11851
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectMechanical Engineeringen_US
dc.subjectSemantic segmentationen_US
dc.subjectInstance Segmentationen_US
dc.subjectAutonomous navigationen_US
dc.subjectIndian Driving Dataseten_US
dc.subjectUnstructured environmenten_US
dc.titleComplete Scene Parsing for Autonomous Navigation in Unstructured Environmentsen_US
dc.typeArticleen_US

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