Custom Lightweight Convolutional Neural Network Architecture for Automated Detection of Damaged Pallet Racking in Warehousing & Distribution Centers

This paper proposes a Convolutional Neural Network–Block Development Mechanism (CNN-BDM) enabling the development of a lightweight deep learning architecture for the detection of damaged pallet-racking, within the manufacturing/warehousing environment. The developed CNN architecture consisted...

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Dades bibliogràfiques

Autors principals:	Muhammad Hussain, Richard Hill
Format:	Artigo
Idioma:	Inglês
Publicat:	IEEE 2023-01-01
Col·lecció:	IEEE Access
Matèries:	Architectural complexities image modelling damage detection lightweight footprint convolutional neural network
Accés en línia:	https://ieeexplore.ieee.org/document/10145104/
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