Efficient Semantic Segmentation for Resource-Constrained
Applications with Lightweight Neural Networks

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Efficient Semantic Segmentation for Resource-Constrained Applications with Lightweight Neural Networks

This thesis focuses on developing lightweight semantic segmentation models tailored for resource-constrained applications, effectively balancing accuracy and computational efficiency. It introduces several novel concepts, including knowledge sharing, dense bottleneck, and feature re-usability, which...

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Bibliographic Details
Main Author:	Singha, Tanmay
Format:	Thesis
Published:	Curtin University 2023
Online Access:	http://hdl.handle.net/20.500.11937/93644

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