The traditional social governance approach is becoming more and more powerless when confronting new governance puzzles. The application of "technology" and "experts" embedded in technological governance helps to promote social efficiency and productivity, which overthrows the traditional ways of governance in the smart city era. Our understanding of how to strengthen the governance capacity and achieve a smarter government, however, is inadequate. Governments are under pressure to provide new public services with modern science and technologies. Motivated by this gap, we develop a vehicle recognition network model of unsupervised learning based on computer image recognition. The key to our theory is that smart technology enables governments to respond more effectively to the need of new public services. Seven iterative experiments were conducted through a large-scale benchmark data set, namely Veri-776 based on the proposed model of vehicle recognition network, and the results were tested to show a good performance, illustrating that image recognition can enhance governance capabilities. This article provides more insights into the knowledge of smart technologies in improving governance capabilities and extends theorization on technological governance by examining their relevance in a computer techniques context.