DETECTION OF SKIN DISEASE IN PERVASIVE HEALTH CARE USING CONVOLUTION NEURAL NETWORK

Sarojini Sharon, Sruthy Simon, R. Moorthy, Dr. P. Pabitha
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Abstract

Abstrac. This paper is about detecting skin disease using convolutional neural network in pervasive health care. Various optimizers in keras model are compared and the optimizer with the highest accuracy percentage is employed to predict skin disease through abnormalities in skin images. Detecting skin diseases by viewing images of skin can be an advancement to a great extent. There are many algorithms in machine language which would help to serve the above mentioned scenario. One of the most efficient algorithms that is being used here is convolutional neural networks. It simplifies the input image by reducing its dimensionality which makes prediction of patterns much easier.Convolutional neural network is used along with keras using tensorflow as backend which enables higher efficiency and accuracy.
基于卷积神经网络的普适医疗皮肤病检测
Abstrac。本文是关于在普适医疗中使用卷积神经网络检测皮肤疾病。比较keras模型中的各种优化器,采用准确率最高的优化器通过皮肤图像中的异常预测皮肤病。通过观察皮肤图像来检测皮肤病在很大程度上是一种进步。在机器语言中有许多算法可以帮助服务于上述场景。这里使用的最有效的算法之一是卷积神经网络。它通过降低输入图像的维数来简化输入图像,从而使模式预测更加容易。卷积神经网络与keras一起使用,使用tensorflow作为后端,提高了效率和准确性。
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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