Detection of Diabetic Retinopathy Using Deep Learning - G., Karpagameenakshi;Juliet, A. Vimala
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  • Broschiertes Buch

In this book, a deep learning technique called Convolution Neural Network (CNN) is deployed for determining the level of DR with accuracy. Hence, for training, this network, fundus image dataset from a public resource called Kaggle is utilized. But, before feeding the dataset into a deep learning model, the images are pre-processed using the libraries present in python, so that the model can accurately classify the test input image into the respective diabetic retinopathy class. Thus, the proposed deep learning model helps in identifying DR automatically at its earlier stage, thus helping in…mehr

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Produktbeschreibung
In this book, a deep learning technique called Convolution Neural Network (CNN) is deployed for determining the level of DR with accuracy. Hence, for training, this network, fundus image dataset from a public resource called Kaggle is utilized. But, before feeding the dataset into a deep learning model, the images are pre-processed using the libraries present in python, so that the model can accurately classify the test input image into the respective diabetic retinopathy class. Thus, the proposed deep learning model helps in identifying DR automatically at its earlier stage, thus helping in controlling its progression that leads to vision-related problems.
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Autorenporträt
Mrs.Karpagam did M. Tech Degree in E&CE, SRM IST, and Works in MNC as Assistant System Engineer. Dr.Juliet started her career as a Research Engineer in FCRI and then switched over to the teaching profession in 1994. She co-authored more than 110 papers, guided 22 doctorates, several PG and UG, recipient of several awards, ISA Fellow in 2016.