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dc.contributor.authorJulio, Castaño-Amoros-
dc.contributor.authorFrancisco, Fuentes-
dc.contributor.authorPablo, Gil-
dc.date.accessioned2023-04-17T03:56:04Z-
dc.date.available2023-04-17T03:56:04Z-
dc.date.issued2023-
dc.identifier.urihttps://dlib.phenikaa-uni.edu.vn/handle/PNK/7984-
dc.descriptionCC BYvi
dc.description.abstractThe paper industry manufactures corrugated cardboard packaging, which is unassembled and stacked on pallets to be supplied to its customers. Human operators usually classify these pallets according to the physical features of the cardboard packaging. This process can be slow, causing congestion on the production line. To optimise the logistics of this process, we propose a visual recognition and tracking pipeline that monitors the palletised packaging while it is moving inside the factory on roller conveyors. Our pipeline has a two-stage architecture composed of Convolutional Neural Networks, one for oriented pallet detection and recognition, and another with which to track identified pallets.vi
dc.language.isoenvi
dc.publisherSpringervi
dc.subjectMOSPPAvi
dc.titleMOSPPA: monitoring system for palletised packaging recognition and trackingvi
dc.typeBookvi
Appears in Collections
OER - Kỹ thuật điện; Điện tử - Viễn thông

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