A Number Recognition Method Based on Improving Lightweight ResNet
Gongming Zheng, Zhiwei Wang · 2023
This paper proposes a lightweight ResNet for highly accurate recognition of the numbers of wheel dials. The proposed residual network is based on an optimized ResNet-18 network with the depthwise separable convolution and Dropout function. In addition, a case study on automatic water meter readings based on captured images is presented. Compared to existing methods, the results demonstrate the improved recognition accuracy of this method is up to 99.8% and increased computation speeds with reduced model parameter size.