Comparative Study of Various Convolutional Neural Networks on Cifar-10

Tushar Goyal
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Abstract

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.
Cifar-10上各种卷积神经网络的比较研究
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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