On 3 November, the Chinese National Science and Technology Awards Conference, a flagship event in the field of Chinese science and technology, opened in Beijing. The project ‘Key Technology Equipment and Application of Automated Processing and Digital Quality Control of Green Tea’ won the National Science and Technology Progress Award again.
In 2006, Meyer’s project ‘SS-type Digital Colour Sorter’ won the second prize for the first time.
The National Science and Technology Progress Award represents China’s cutting-edge development in science and technology.

National Science and Technology Progress Award Premio Nacional al Progreso en Ciencia y Tecnología

Focusing on the lack of quality control, automatic processing technology and equipment in the green tea industry, the award-winning project adopts the “digital quality control – automated processing – systematic technology” method to develop key technical equipment for automatic processing and digital quality control of green tea.
It will be applied in major tea areas in China, Thailand, India and other countries.

Meyer is always committed to leading the industry’s technological progress and high-quality development with high standards, focusing on the three main business fields of agricultural product sorting, industrial X-ray inspection and high-end medical imaging equipment .

With three major innovation platforms, including the National Engineering Technology Research Center, the National Certified Enterprise Technology Center and the National Post-doctoral Research Workstation, a market-oriented innovation system with deep industry-academia-research-application integration It is built in a global perspective, which accelerates the transformation of the results of industry-university-research cooperation.

Meyer delivers greater contributions to society and people, and greater value for customers.

Identifying impurities and defects with deep learning

Impurities or defects that can be identified by the human eye are difficult to define using traditional algorithms.
The deep learning platform of our sorters, however, also solves this problem!

Meyer’s deep learning is based on a large database of samples.
It will immediately be possible to calibrate complex details such as:

  • color;
  • form;
  • textures;
  • etc.

 

This will only be the beginning!
Based on the customer’s needs, our technology will be able to learn by building and iterating (repeating) increasingly precise selection models.

With independent learning you will obtain precise analysis, identification and selection of materials, satisfying the customer’s selection needs.

The 7 steps to take to take advantage of Meyer deep learning in systems:

  1. Equipment: upgrade and/or equip yourself with our deep learning technology;

  2. Data collection: after the first selections, a large number of high-definition photos of foreign bodies and defects will be collected, thus creating a database;

  3. Calibration: Mayer’s deep learning platform automatically calibrates the machine based on images of foreign objects and defects;

  4. Solution Generation: The platform is now capable of generating solutions by leveraging the technology embedded in the machines;

  5. Automatic machine learning: the sorter autonomously learns the characteristics of the data, identifying defects;

  6. Verification of results: it will be possible to immediately verify the solutions developed by deep learning to analyze the effects on selection;

  7. Optimization: possibility of making further optimizations for any new needs.

deep learning esempi

For any information our team is at your complete disposal.

Those who look to the future choose Meyer!