Application development for product recognition on-shelf with deep learning
Negligence of empty shelf and high human intervention have been the issues that leads to low customer retention in brick-and-mortar stores. Hence, state-ofthe-art deep learning models are trained and compared for product recognition on-shelf and an application to detect empty shelf with the best dee...
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| Format: | Final Year Project / Dissertation / Thesis |
| Published: |
2022
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| Online Access: | http://eprints.utar.edu.my/5016/1/1906365_EYU_JER_MIN.pdf http://eprints.utar.edu.my/5016/ |
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