首页> 外文会议>International Conference on Intelligent Technologies >Severity Classification of Diabetic Retinopathy using ShuffleNet
【24h】

Severity Classification of Diabetic Retinopathy using ShuffleNet

机译:使用Shuffleenet的糖尿病视网膜病变的严重程度分类

获取原文

摘要

In India, the number of people living with diabetes is about 72.96 million and large proportion of people suffer from Diabetic Retinopathy which is caused due to elevated level of blood sugar in a diabetic patient that can harm the retina of person and may lead to permanent blindness. The detection of Diabetic Retinopathy is being practiced in such a way that it still needs complex human efforts. The need of the hour is to discover new and better methods that can help further improve identification and treatment of DR (Diabetic Retinopathy). This paper proposes a different method and model to identify and distinguish DR into various severity levels. A novel approach is introduced to detect Diabetic Retinopathy using Shufflenetv2 which is Convolutional neural network. The results are better when compared to other models in literature. Smooth L2 loss function has been used to depict the errors and analyze the results.
机译:在印度,糖尿病的人数约为72.96亿,大部分人群患有糖尿病视网膜病变,这是由于糖尿病患者血糖水平升高,这可能会损害人的视网膜,可能导致永久失明 。 糖尿病视网膜病变的检测是为了使其仍然需要复杂的人类努力。 小时的需要是发现可以帮助进一步改善博士(糖尿病视网膜病变)的鉴定和治疗的新方法。 本文提出了一种不同的方法和模型来识别和将DR区分成各种严重程度。 引入一种新的方法来使用卷积神经网络的Shufflenetv2检测糖尿病视网膜病变。 与文献中的其他模型相比,结果更好。 平滑的L2损耗功能已被用于描述误差并分析结果。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号