The layout about pressure plate of relay protection devices is gradually changing towards simplicity and standardization, which objectively provides conditions for intelligent inspection of the pressure plate. However, due to the actual scene, it is often impossible to provide pressure plate images with sufficient size and resolution for pressure plate recognition. To this end, a method based on image enhancement and deep neural network for target recognition is proposed to recognize pressure plate images with low resolution. The image enhancement network uses collaborative learning signals from the target recognition network to enhance extremely low-resolution images into clearer and more informative images, so that the target recognition network with high-resolution image training weights actively participates in the learning of the image enhancement network; and then the output of the image enhancement network is utilized as enhanced learning data, to improve the recognition performance for very low-resolution objects. Experiments on various benchmark datasets with low-resolution image verify that this method can improve the reconstruction and classification performance of pressure plate images.