Advancements in Image Classification using Convolutional Neural Network

被引：0

作者：

Sultana, Farhana ^{[1
]}

Sufian, Abu ^{[1
]}

Dutta, Paramartha ^{[2
]}

机构：

[1] Univ Gour Banga, Dept Comp Sci, Malda, W Bengal, India

[2] Visva Bharati Univ, Dept CSS, Santini Ketan, W Bengal, India

来源：

2018 FOURTH IEEE INTERNATIONAL CONFERENCE ON RESEARCH IN COMPUTATIONAL INTELLIGENCE AND COMMUNICATION NETWORKS (ICRCICN) | 2018年

关键词：

AlexNet; Capsnet; Convolutional Neural Network; Deep learning; DenseNet; Image classification; ResNet; SENet; RECOGNITION;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Convolutional Neural Network (CNN) is the state-of-the-art for image classification task. Here we have briefly discussed different components of CNN. In this paper, We have explained different CNN architectures for image classification. Through this paper, we have shown advancements in CNN from LeNet-5 to latest SENet model. We have discussed the model description and training details of each model. We have also drawn a comparison among those models.

引用

页码：122 / 129

页数：8

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