The invention proposes a convolutional neural network acceleration method based on the OpenCL standard for mainly solving the problem of low efficiency of the existing CPU to process a convolutional neural network. The method comprises the following steps: 1, reading original three-dimensional image data, and transmitting the original three-dimensional image data to a global memory of a GPU; 2, reading weights and offset data in the global memory of the GPU; 3, reading the original image data in the global memory of the GPU in a local memory of the GPU; 4, initializing the parameters, and constructing a linear activation function Leaky-ReLU; 5, calculating picture data of the twelfth layer of the convolutional neural network; 6, calculating the picture data of the fifteenth layer of the convolutional neural network; and 7, calculating the picture data of the eighteenth layer of the convolutional neural network, storing the picture data in the GPU, transmitting the picture data to a host memory, and providing an operation time. By adoption of the convolutional neural network acceleration method, the operation speed of the convolutional neural network is improved, and the convolutional neural network acceleration method can be applied to object detection in computer vision.