Da: California Books, Miami, FL, U.S.A.
EUR 47,80
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
Da: California Books, Miami, FL, U.S.A.
EUR 47,80
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
Da: PBShop.store US, Wood Dale, IL, U.S.A.
EUR 60,31
Quantità: Più di 20 disponibili
Aggiungi al carrelloPAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
Da: PBShop.store UK, Fairford, GLOS, Regno Unito
EUR 57,89
Quantità: Più di 20 disponibili
Aggiungi al carrelloPAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
Da: Revaluation Books, Exeter, Regno Unito
EUR 50,06
Quantità: 2 disponibili
Aggiungi al carrelloPaperback. Condizione: Brand New. 118 pages. 6.00x0.27x9.00 inches. In Stock.
Da: Revaluation Books, Exeter, Regno Unito
EUR 50,12
Quantità: 2 disponibili
Aggiungi al carrelloPaperback. Condizione: Brand New. 98 pages. 6.00x0.23x9.00 inches. In Stock.
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
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 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. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Da: Majestic Books, Hounslow, Regno Unito
EUR 72,13
Quantità: 4 disponibili
Aggiungi al carrelloCondizione: New. Print on Demand.
Da: Majestic Books, Hounslow, Regno Unito
EUR 73,15
Quantità: 4 disponibili
Aggiungi al carrelloCondizione: New. Print on Demand.
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 75,08
Quantità: 4 disponibili
Aggiungi al carrelloCondizione: New. PRINT ON DEMAND.
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 75,97
Quantità: 4 disponibili
Aggiungi al carrelloCondizione: New. PRINT ON DEMAND.
Da: CitiRetail, Stevenage, Regno Unito
EUR 63,64
Quantità: 1 disponibili
Aggiungi al carrelloPaperback. 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 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Da: AussieBookSeller, Truganina, VIC, Australia
EUR 83,30
Quantità: 1 disponibili
Aggiungi al carrelloPaperback. 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 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. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 61,73
Quantità: 1 disponibili
Aggiungi al carrelloTaschenbuch. 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.
Da: preigu, Osnabrück, Germania
EUR 53,85
Quantità: 5 disponibili
Aggiungi al carrelloTaschenbuch. 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 Print on Demand.