Dog Breed Identification Using Deep Learning

Zalán Ráduly, Csaba Sulyok, Zsolt Vadászi, Attila Zolde
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引用次数: 15

Abstract

The current paper presents a fine-grained image recognition problem, one of multi-class classification, namely determining the breed of a dog in a given image. The presented system employs innovative methods in deep learning, including convolutional neural networks. Two different networks are trained and evaluated on the Stanford Dogs dataset. The usage/evaluation of convolutional neural networks is presented through a software system. It contains a central server and a mobile client, which includes components and libraries for evaluating on a neural network in both online and offline environments.
利用深度学习识别狗的品种
本文提出了一个细粒度图像识别问题,即多类分类问题之一,即在给定图像中确定狗的品种。该系统采用了深度学习的创新方法,包括卷积神经网络。在斯坦福狗的数据集上训练和评估了两个不同的网络。通过一个软件系统介绍了卷积神经网络的使用和评价。它包含一个中央服务器和一个移动客户端,其中包括用于在线和离线环境下对神经网络进行评估的组件和库。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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