Arrival Parcel/3D Bulk Flow Detection System
Arrival Parcel/3D Bulk Flow Detection System
Application scenario
System Introduction
The system relies on deep learning target detection and real-time multi-target tracking technologies to identify, remove, and return stacked parcels to the abnormal parcel processing area. This system is widely used in the middle and back ends of automated sorting systems.
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Accuracy rate of arrival parcel detection
≥ 99.9%
Accuracy rate of 3D bulk flow detection
≥ 99.5%
Product Display
Competitive Advantage
Casestudy
Competitive Advantage
Break through the traditional technology bottleneck with accurate identification for stacked thin parcels
The problem that stacked thin parcels cannot be detected by the conventional photoelectric detection methods is solved, with an accuracy rate of arrival parcel detection ≥99.9% and an accuracy rate of 3D bulk flow detection ≥99.5%.
Solve recognition problems such as reflections for ultra-thin parcels through data model training
By using machine learning and deep learning algorithms, models are trained with large amounts of data to recognize the features of ultra-thin parcels, solving the problem of difficult recognition caused by the reflections and unclear textures of some ultra-thin parcels.
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