Retinal (Glaucoma) Image Synthesis: Using Traditional and Advanced Data Augmentation Techniques - Softcover
Synopsis
The human eye is an organ that reacts to light and pressure. Many diseases, disorders, and age-related changes may affect the eyes and surrounding structures. One of the eye diseases is glaucoma. Glaucoma is a condition in which fluid pressure rises within the eye. Without treatment, it can damage the optic nerve and lead to vision loss. The early detection of glaucoma minimizes the risk of vision loss. The proposed model synthesizes highly realistic controllable fundus images to obtain precision in detecting glaucoma through a deep learning model.A generative adversarial network (GAN) is an unsupervised machine learning technique that can be used to augment datasets and yield collected images to be indistinguishable from real-world data. The Deep Convolutional GAN (DCGAN), another variant of GAN, suggests the architectural constraints on the model required to develop high-quality generator models effectively. The enhanced dataset, obtained from data augmentation and the original ACRIMA dataset of fundus images, are separately given to the CNN classification model for detecting glaucoma disease.
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Retinal (Glaucoma) Image Synthesis: Using Traditional and Advanced Data Augmentation Techniques
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ISBN 13: 9786206737384
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Retinal (Glaucoma) Image Synthesis: Using Traditional and Advanced Data Augmentation Techniques
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Retinal (Glaucoma) Image Synthesis: Using Traditional and Advanced Data Augmentation Techniques
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Retinal (Glaucoma) Image Synthesis
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The human eye is an organ that reacts to light and pressure. Many diseases, disorders, and age-related changes may affect the eyes and surrounding structures. One of the eye diseases is glaucoma. Glaucoma is a condition in which fluid pressure rises within the eye. Without treatment, it can damage the optic nerve and lead to vision loss. The early detection of glaucoma minimizes the risk of vision loss. The proposed model synthesizes highly realistic controllable fundus images to obtain precision in detecting glaucoma through a deep learning model.A generative adversarial network (GAN) is an unsupervised machine learning technique that can be used to augment datasets and yield collected images to be indistinguishable from real-world data. The Deep Convolutional GAN (DCGAN), another variant of GAN, suggests the architectural constraints on the model required to develop high-quality generator models effectively. The enhanced dataset, obtained from data augmentation and the original ACRIMA dataset of fundus images, are separately given to the CNN classification model for detecting glaucoma disease. 60 pp. Englisch. Seller Inventory # 9786206737384
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Retinal (Glaucoma) Image Synthesis
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The human eye is an organ that reacts to light and pressure. Many diseases, disorders, and age-related changes may affect the eyes and surrounding structures. One of the eye diseases is glaucoma. Glaucoma is a condition in which fluid pressure rises within . Seller Inventory # 982870175
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Retinal (Glaucoma) Image Synthesis
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The human eye is an organ that reacts to light and pressure. Many diseases, disorders, and age-related changes may affect the eyes and surrounding structures. One of the eye diseases is glaucoma. Glaucoma is a condition in which fluid pressure rises within the eye. Without treatment, it can damage the optic nerve and lead to vision loss. The early detection of glaucoma minimizes the risk of vision loss. The proposed model synthesizes highly realistic controllable fundus images to obtain precision in detecting glaucoma through a deep learning model.A generative adversarial network (GAN) is an unsupervised machine learning technique that can be used to augment datasets and yield collected images to be indistinguishable from real-world data. The Deep Convolutional GAN (DCGAN), another variant of GAN, suggests the architectural constraints on the model required to develop high-quality generator models effectively. The enhanced dataset, obtained from data augmentation and the original ACRIMA dataset of fundus images, are separately given to the CNN classification model for detecting glaucoma disease.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 60 pp. Englisch. Seller Inventory # 9786206737384
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Retinal (Glaucoma) Image Synthesis : Using Traditional and Advanced Data Augmentation Techniques
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ISBN 10: 6206737381
ISBN 13: 9786206737384
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The human eye is an organ that reacts to light and pressure. Many diseases, disorders, and age-related changes may affect the eyes and surrounding structures. One of the eye diseases is glaucoma. Glaucoma is a condition in which fluid pressure rises within the eye. Without treatment, it can damage the optic nerve and lead to vision loss. The early detection of glaucoma minimizes the risk of vision loss. The proposed model synthesizes highly realistic controllable fundus images to obtain precision in detecting glaucoma through a deep learning model.A generative adversarial network (GAN) is an unsupervised machine learning technique that can be used to augment datasets and yield collected images to be indistinguishable from real-world data. The Deep Convolutional GAN (DCGAN), another variant of GAN, suggests the architectural constraints on the model required to develop high-quality generator models effectively. The enhanced dataset, obtained from data augmentation and the original ACRIMA dataset of fundus images, are separately given to the CNN classification model for detecting glaucoma disease. Seller Inventory # 9786206737384
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Retinal (Glaucoma) Image Synthesis | Using Traditional and Advanced Data Augmentation Techniques
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Taschenbuch. Condition: Neu. Retinal (Glaucoma) Image Synthesis | Using Traditional and Advanced Data Augmentation Techniques | Sravani Devi Yerrarapu | Taschenbuch | Englisch | 2023 | LAP LAMBERT Academic Publishing | EAN 9786206737384 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 127329315
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