traditional corn analysis methods:
Manual sampling, inspection, recording and statistics, slow efficiency, low accuracy, high miss rate and false detection rate, long-term fatigue, can not meet the actual production needs. Inspectors are easy to collude with suppliers, which is not conducive to corn quality control.
The equipment analysis method:
Combined with the traditional machine vision method and artificial intelligence algorithm to analyze the corn, first of all, the traditional visual met

Traditional wheat analysis method
Manual sampling, inspection, recording and statistics, slow efficiency, low accuracy, high miss rate and false detection rate, long-term fatigue, can not meet the actual production needs. It is easy for inspectors to collude with suppliers, which is not conducive to wheat quality control.
Analysis method of this equipment
Combined with the traditional machine vision method and artificial intelligence algorithm to analyze the wheat, first of all, the traditional

traditional coffee beans analysis method:
Manual sampling, inspection, recording and statistics, slow efficiency, low accuracy, high miss rate and false detection rate, long-term fatigue, can not meet the actual production needs. The inspectors are easy to collude with the supplier, which is not conducive to the quality of coffee beans.
The equipment analysis method:
Combining the traditional machine vision method and artificial intelligence algorithm to analyze the coffee beans, the traditional

traditional rice analysis methods:
Manual sampling, inspection, recording and statistics, slow efficiency, low accuracy, high miss rate and false detection rate, long-term fatigue, can not meet the actual production needs. Inspectors are easy to collude with suppliers, which is not conducive to the quality of rice.
The equipment analysis method:
Combined with the traditional machine vision method and artificial intelligence algorithm to analyze the rice, first of all, the traditional visual meth