基于卷积神经网络算法的图像识别应用研究

Research on Application of Image Recognition Based on the Convolutional Neural Network Algorithm

研究了基于卷积神经网络算法的图像识别应用,以人工神经网络为基础,形成卷积神经网络.通过卷积运算的数学方法,利用ORL人脸数据集,进行对比实验,对误差曲线进行研究.结果表明:识别技术虽已趋于稳定,但仍存在内存不足的问题,主要存在单机串行方式实现和训练时间过长的问题.卷积神经网络广泛应用于图像识别领域,并且在物体检测和语音识别领域也得到了应用.

The application of image recognition based on the convolutional neural network algorithm is studied.The convolutional neural network is formed on the basis of artificial neural network.The mathematical method of convolution operation,ORL face data set,error curve drawing and comparative experiments are used to study.The research shows that although the recognition technology has become stable,there are still some problems of insufficient memory,mainly the problem of single-machine serial mode implementation,and the problem of too long training time also exists.In conclusion,the convolutional neural network is widely used in the field of image recognition,and it has also been applied in the field of object detection and speech recognition.