Cifar-10上各种卷积神经网络的比较研究

International Journal for Modern Trends in Science and Technology Pub Date : 2020-12-18 DOI:10.46501/ijmtst061276

Tushar Goyal

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引用次数: 0

摘要

图像识别在计算机视觉领域中起着基础性的作用，并且已经有广泛的研究来开发最先进的技术，特别是使用卷积神经网络(CNN)。本文旨在研究一些cnn，这些cnn很大程度上受到了非常流行的最先进的cnn的启发，专门为Cifar-10数据集设计，并在它们之间进行公平的比较。

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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Comparative Study of Various Convolutional Neural Networks on Cifar-10

Image recognition plays a foundational role in the field of computer vision and there has been extensive research to develop state-of-the-art techniques especially using Convolutional Neural Network (CNN). This paper aims to study some CNNs, heavily inspired by highly popular state-of-the-art CNNs, designed from scratch specifically for the Cifar-10 dataset and present a fair comparison between them.

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International Journal for Modern Trends in Science and Technology

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