9786203306064 - diabetic retinopathy: automatic detection of diabetic retinopathy in retinal images using neural network de shaik, shafiulla basha; syed, jahangir badashah (5 resultados)
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Librería: preigu, Osnabrück, Alemaniapreigu
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Taschenbuch. Condición: Neu. Diabetic Retinopathy | Automatic Detection of Diabetic Retinopathy in Retinal Images Using Neural Network | Shafiulla Basha Shaik (u. a.) | Taschenbuch | Englisch | 2021 | LAP LAMBERT Academic Publishing | EAN 9786203306064 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landst…r. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -As a weakly supervised learning technique, neural network (NN) has shown an advantage over supervised learning methods for automatic detection of diabetic retinopathy (DR): only the image-level annotation is needed to achieve both d…etections of DR images and DR lesions, making more graded and de-identified retinal images available for learning. However, the performance of existing studies on this technique is limited by the use of handcrafted features. We propose a NN method for DR detection, which jointly learns features and classifiers from data and achieves a significant improvement on detecting DR images and their inside lesions. Specifically, a pre-trained neural network is adapted to achieve the patch-level DR estimation, and then global aggregation is used to make the classification of DR images. 72 pp. Englisch.
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Librería: moluna, Greven, Alemaniamoluna
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Shaik Shafiulla BashaDr. S. Shafiulla Basha is working as an Assistant Professor in the Department of ECE at Y.S.R. Engineering College of Yogi Vemana University, Proddatur, India. He published 20 resea…rch articles in various journal.
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -As a weakly supervised learning technique, neural network (NN) has shown an advantage over supervised learning methods for automatic detection of diabetic retinopathy (DR): only the image-level annotation is needed to achieve both detec…tions of DR images and DR lesions, making more graded and de-identified retinal images available for learning. However, the performance of existing studies on this technique is limited by the use of handcrafted features. We propose a NN method for DR detection, which jointly learns features and classifiers from data and achieves a significant improvement on detecting DR images and their inside lesions. Specifically, a pre-trained neural network is adapted to achieve the patch-level DR estimation, and then global aggregation is used to make the classification of DR images.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 72 pp. Englisch.
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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EUR 40,89
Envío por EUR 60,63Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - As a weakly supervised learning technique, neural network (NN) has shown an advantage over supervised learning methods for automatic detection of diabetic retinopathy (DR): only the image-level annotation is needed to achieve both detect…ions of DR images and DR lesions, making more graded and de-identified retinal images available for learning. However, the performance of existing studies on this technique is limited by the use of handcrafted features. We propose a NN method for DR detection, which jointly learns features and classifiers from data and achieves a significant improvement on detecting DR images and their inside lesions. Specifically, a pre-trained neural network is adapted to achieve the patch-level DR estimation, and then global aggregation is used to make the classification of DR images.
