In the environment of rapid development of technology, scientific research, processing, manufacturing and other fields are also developing in the direction of richer functions and more sophisticated design, and the requirements for the properties of various parts are becoming increasingly strict. In the field of electronic information, the small resistance of a part also deeply affects the quality of the product. In this paper, a set of micro resistance measurement system based on MCU is completed by combining the relevant knowledge of MCU with resistance measurement technology. The micro resistance measurement system based on STC89C52 single chip microcomputer is designed to provide better experience for users, and intelligent products are designed around customer needs. A micro resistance measurement system including LCD module and resistance measurement module is designed. The micro resistance measurement system based on SCM designed in this paper effectively reduces the system volume, improves the portability of the system, effectively reduces the production cost, has high measurement accuracy, and makes the system easy to use. It is a convenient and fast integrated design of SCM system that can adapt to various workplaces.
Aiming at the demand of visual detection equipment for miniature target detection system, in order to improve the calculation accuracy and speed of the target detection platform, a target detection method based on FPGA convolution neural network is developed. The characteristics of convolutional neural network and its structural characteristics are analyzed, Convolutional neural network is applied in micro target detection the appropriate convolutional neural network model is selected according to the requirements and the model parameters are obtained. This model can embed the algorithm into the hardware platform system with high performance FPGA chip as its underlying core structure, and can achieve efficient effect. The experimental results can also prove that the real-time performance of the calculation results in this paper is relatively good, and the processing workload of hardware transplantation is relatively small, which can achieve the effect of effectively detecting the target, solve the problem of high power consumption and insufficient realtime performance of the current special image processor (GPU), and meet the requirements of fast and accurate.
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