基于集成卷积神经网络的场景识别实例研究

B. Oh, Junhyeok Lee
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引用次数: 5

摘要

本文提出了基于两个卷积神经网络集成的场景图像识别体系结构。一种卷积神经网络用于训练海量场景图像,另一种卷积神经网络用于从场景图像中提取目标。根据场景分类存储目标列表,作为场景图像识别阶段确定top-1和top-5类的线索。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A case study on scene recognition using an ensemble convolution neural network
This paper proposes architecture to recognize scene images based on an ensemble of two convolution neural networks. A convolution neural network is used to train massive scene images, and the other convolution neural network is used to extract objects from the scene images. The object lists are stored according to scene classes, and used as a clue to decide the top-1 and top-5 classes during scene image recognition stage.
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