9789999328296 - design and development of a medical image diagnosis system based on machine learning: deep learning-powered breast cancer classification using resnet50 and the breakhis dataset di tulla, md hamid borkot (8 risultati)
- Brossura
Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 60,15
EUR 3,87 spedizioneSpedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
- Brossura
Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 61,49
EUR 11,77 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 2 disponibili
Paperback. Condizione: Brand New. 98 pages. 6.00x0.23x9.00 inches. In Stock.
- Brossura
- Print on Demand
Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 72,13
EUR 7,65 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 4 disponibili
Condizione: New. Print on Demand.
- Brossura
- Print on Demand
Da: Books Puddle, New York, NY, U.S.A.Books Puddle
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 76,75
EUR 3,49 spedizioneSpedito in U.S.A.Quantità: 4 disponibili
Condizione: New. Print on Demand.
- Brossura
- Print on Demand
Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 72,25
EUR 9,95 spedizioneSpedito da Germania a U.S.A.Quantità: 4 disponibili
Condizione: New. PRINT ON DEMAND.
- Brossura
- Print on Demand
Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 65,43
EUR 43,53 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Paperback. Condizione: new. Paperback. "Design and Development of a Medical Image Diagnosis System Based on Machine Learning" by Md. Hamid Borkot Tulla is a pioneering undergraduate research project aimed at transforming breast cancer diagnosis. Leveraging the power of deep learning and transfer learning, this study deploys a fi…ne-tuned ResNet50 convolutional neural network on the renowned BreaKHis dataset to classify histopathological breast tissue images as benign or malignant. The model achieved a remarkable accuracy of 81.28% and recall of 94.65%, providing reliable diagnostic support in clinical workflows. This research not only offers a practical AI-driven decision-support system for pathologists but also lays the groundwork for future multi-class classification models and real-time clinical integration in resource-constrained healthcare settings. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
- Brossura
- Print on Demand
Da: preigu, Osnabrück, Germaniapreigu
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 53,85
EUR 70,00 spedizioneSpedito da Germania a U.S.A.Quantità: 5 disponibili
Taschenbuch. Condizione: Neu. Design and Development of a Medical Image Diagnosis System Based on Machine Learning | MD Hamid Borkot Tulla | Taschenbuch | Englisch | 2025 | Eliva Press | EAN 9789999328296 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu P…rint on Demand.
- Brossura
- Print on Demand
Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 63,76
EUR 60,80 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 'Design and Development of a Medical Image Diagnosis System Based on Machine Learning' by Md. Hamid Borkot Tulla is a pioneering undergraduate research project aimed at transforming breast cancer diagnosis. Leveraging the power of deep…learning and transfer learning, this study deploys a fine-tuned ResNet50 convolutional neural network on the renowned BreaKHis dataset to classify histopathological breast tissue images as benign or malignant. The model achieved a remarkable accuracy of 81.28% and recall of 94.65%, providing reliable diagnostic support in clinical workflows. This research not only offers a practical AI-driven decision-support system for pathologists but also lays the groundwork for future multi-class classification models and real-time clinical integration in resource-constrained healthcare settings.
