卷积神经网络

  • 网络convolutional neural network
卷积神经网络卷积神经网络
  1. 我们先利用改进的K-means聚类方法从训练数据中获得基向量,再结合卷积神经网络提取字符图像的特征。

    Firstly , we use the variant of K-means obtain the basis vectors from the training data , then extract character feature by combining convolutional neural network . 2 .

  2. 为了提高人工神经网络处理动态信号能力,在时延神经网络(TDNN)和卷积神经网络(CNN)的基础上,针对孤立音节的特点,提出了一个新的网络结构,研究了其学习算法。

    The ability of neural networks to deal with time dynamic signal was improved with a new neural network architecture specializing in syllable recognition based on the time delay neural network ( TDNN ) and the convolutional neural network .

  3. 增长式卷积神经网络及其在人脸检测中的应用

    Incremental Convolution Neural Network and Its Application in Face Detection

  4. 在得到桥牌的位置后,应用卷积神经网络来分类桥牌。

    Then , a convolutional neural network is utilized to classify the cards .

  5. 基于卷积神经网络的模式分类器

    Building pattern classifiers with convolutional neural networks

  6. 本文通过训练卷积神经网络,使其自行学习样本中内在特征,以达到识别单个手写数字的目的。

    In this paper , by training the convolutional neural network , the network can learn the the inner features automatically so that it can recognise these digital accurately .

  7. 安德雷·卡帕西,斯坦福一个研究计算机深度学习的博士生,决定使用包含1.4亿个参数的强大卷积神经网络来研究为何有的自拍更受欢迎。

    Andrej Karpathy , a PhD student at Stanford working on Deep Learning , decided to use a powerful , 140-million-parameter state-of-the-art Convolutional Neural Network to help work out why some selfies are more popular than other .

  8. 长约束度卷积码译码器神经网络结构

    A Neural Network Architecture for the Decoding of Long Constraint Length Convolutional Codes