使用TensorFlow深度学习-卷积神经网络理解图像分类

Vinit Kumar Gunjan, Rashmi Pathak, Omveer Singh
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引用次数: 2

摘要

本文描述了如何在卷积神经网络(CNN)训练中建立各种图像分组的神经网络技术。此外,本文还提出了利用CNN学习特性对不同类别图像进行分类的初步分类结果。为了确定正确的架构,我们探索了一种迁移学习技术,称为深度学习技术的微调,这是一个用于为单独分类的图像类提供解决方案的数据集。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Understanding Image Classification Using TensorFlow Deep Learning - Convolution Neural Network
This article describes how to establish the neural network technique for various image groupings in a convolution neural network (CNN) training. In addition, it also suggests initial classification results using CNN learning characteristics and classification of images from different categories. To determine the correct architecture, we explore a transfer learning technique, called Fine-Tuning of Deep Learning Technology, a dataset used to provide solutions for individually classified image-classes.
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