Image Classification Based on Convolutional Neural Network

被引：0

作者：

Prassanna, P. Lakshmi ^{[1
]}

Sandeep, S. ^{[1
]}

Rao, Kantha ^{[1
]}

Sasidhar, T. ^{[1
]}

Lavanya, D. Ragava ^{[1
]}

Deepthi, G. ^{[1
]}

SriLakshmi, N. Vijaya ^{[1
]}

Mounika, P. ^{[1
]}

Govardhani, U. ^{[1
]}

机构：

[1] Koneru Lakshmaiah Educ Fdn, Dept Comp Sci & Engn, Vaddeswaram, AP, India

来源：

SUSTAINABLE COMMUNICATION NETWORKS AND APPLICATION, ICSCN 2021 | 2022年 / 93卷

关键词：

Image classification; Data resources; Testing data; Pooling layers; Convolutional neural networks;

D O I：

10.1007/978-981-16-6605-6_64

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The main goal of this research work is to use Neural Networks to recognize and categorize images. As an input, a fixed dataset will be selected. Further, this research work will consider two distinct types of creatures and determine the animal species. The difficulty of recognizing images of animals is used to solve the CAPTCHA challenge. It is simple and easy, but data shows that cats and dogs are particularly difficult to distinguish automatically. CNNs are the simple neural networks with at least one layer that use convolution rather than generic environment multiplication. We shall visualize and distinguish a code made up of 0's and 1's that is taken- cat as 0 and Dog as 1. This research work aims to train the neural network and recognize the animals. As a result, it demonstrates that such animal finding may be completed by a convolution neural network.

引用

页码：833 / 842

页数：10

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