Focusing on the shortage of structure and training methods of existing classifier, a weakly supervised hierarchical deep learning vehicle recognition algorithm with 2D deep belief networks(2D-DBN) is proposed. Firstly, the traditional one-dimensional deep belief network(DBN) is expanded to 2D-DBN, thus the pixel matrix of the 2-D images is taken as the input. Then, a determination regularization term with proper weight is introduced to the traditional unsupervised training objective function. By this change, the original unsupervised training is transferred to the weakly supervised training, so that the extracted features have more discrimination ability. Multiple sets of comparative experiments show that the proposed algorithm is better than other deep learning algorithms in respect of recog nition rate.