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convolution neural

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卷积神经
Discover how to use convolution neural networks for image classification by taking a set of images as input and automatically detecting emotions in those images.
您将了解如何使用面向图像识别的卷积神经网络,即输入一系列图像后该网络自动检测图像中的情绪。
Firstly, fast positioning is realized by reducing the spatial distance sampling of 3D CT images and matching with 3D convolution neural network.
首先通过缩小三维CT影像空间距离采样,配合3D卷积神经网络实现快速定位。
The thoracic multi-organ segmentation system invented by Tencent Youtu TencentX team provides a fully automated healthy organ segmentation method based on convolution neural network structure, which can accurately and quickly segment healthy organs located near target tumors in thoracic cavity.
由腾讯优图TencentX团队提出的胸部多器官分割系统,提供了一种全自动化的基于卷积神经网络结构的健康器官分割方法,能够精确快速地分割出胸腔内位于靶肿瘤附近的健康器官。
Convolution neural networks are very good at classifying images.
卷积神经网络非常擅长图像分类。
Developers have the option of initiating projects with a Convolution Neural Network model, based Caffe or TensorFlow frameworks, using one of the multiple examples networks.
开发人员可以选择使用基于 Caffe 或 TensorFlow 框架的卷积神经网络模型启动项目,并使用多个示例网络之一。
PolSAR Terrain Classification Based on Fine-tuned Dilated Group-cross Convolution Neural Network
基于精调的膨胀编组-交叉CNN的PolSAR地物分类
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