Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Implementing Deep Learning in Logistics Processes for Damaged Goods Detection
Increasing customers’ demand reflects with the growth of production, which imposes more and more demand on logistics and supply chain management, and making it very complex. In order to keep their customers, companies need to ship their products as fast as possible and in a good condition. This paper proposes a deep learning-based solution for detecting damaged goods before they are shipped to their final destination, thus saving very valuable time, resources and money.
Implementing Deep Learning in Logistics Processes for Damaged Goods Detection
Increasing customers’ demand reflects with the growth of production, which imposes more and more demand on logistics and supply chain management, and making it very complex. In order to keep their customers, companies need to ship their products as fast as possible and in a good condition. This paper proposes a deep learning-based solution for detecting damaged goods before they are shipped to their final destination, thus saving very valuable time, resources and money.
Implementing Deep Learning in Logistics Processes for Damaged Goods Detection
Trendov, Simeon (Autor:in) / Stoilkovska, Emilija (Autor:in) / Mitkovska Trendova, Katerina (Autor:in)
21.02.2022
1513339 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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