About US
Keye Technology relies on the Keye Laboratory of Pattern Recognition of the University of Science and Technology of China, and has a high-level doctoral R&D team covering the entire technology chain of optics, mechanics, electricity, computing and software.
Through the project practice in the fields of packaging containers, 3C, medicine, textile, food, etc., the KVS-AI software and hardware platform has been created, so that AI technology can be transformed into real productivity. We provide visual imaging, algorithm computing power and automatic control AI system solutions for various sub-industries.
Inspection Principle
KEYE Camera inspection system consists of material handling system, vision system, software system, central control system and execution system. The detected objects are sorted through the material sorting system to ensure that the detected objects are oriented in the same direction and evenly distributed.
Then enter the vision system to take 360° images of the detected objects, and transmit the image data to the software system to identify the detected objects. Sorting, issuing rejection and sorting instructions to the execution system.
Equipment Features
| 1.AI algorithm: high stability, adapting to the environment and background disturbance; different defect samples can be automatically identified after training |
| 2.Dataization: Independent database, save multiple samples, analyze non-good products, and retain history |
| 3.Multi-orientation: 360 degree comprehensive inside and outside the samples |
| 4.High precision: detection accuracy can be high |
| 5.Modularization, can flexibly increase or decrease the detection function according to customer actual needs |
| 6.Easy to operate: It is easy to operate and easy to maintain |
| 7.Safety: Medical grade material manufacturing, fully compliant with medical supplies production environment |
Core Technology
- Automatic Binarization: use deep neural network to segment the foreground and background of the image, smoothly segment the grain edge, and accurately locate the grain to be analyzed.
- Adhesion material segmentation algorithm: deep neural network segments the adhering grains to form independent and complete grains, which are analyzed and classified.
- Multi-attribute recognition: It adopts a lightweight neural network and integrates a semi-supervised multi-attribute learning method. The user can label a small number of samples of the grain to be analyzed, and then the data model can be updated to perform fast and high-precision analysis of the grain.
After-sale Service
The company has a complete technical service team and rapid response mechanism, and has dedicated service specialists for each customer, who can receive technical consultation and fault reports from customers at any time. And to ensure rapid response to customer emergencies, to ensure that customers receive satisfactory service.During the epidemic or due to special reasons, when after-sales engineers are unable to reach the site, the service center can remotely adjust customer equipment for troubleshooting and technical consultation.
After the equipment arrives at the customer site, the after-sales engineer arrives in time to carry out equipment installation, commissioning, and operation training. The product quality of the whole machine is traceable, and the quality warranty period is 1 year from the date of acceptance. In the event of non-human faults during the warranty period, after-sales engineers will quickly arrive at the site or provide remote guidance for free maintenance.
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