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A Deep Learning Approach for Recognition Systems
Da: California Books, Miami, FL, U.S.A.
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Condizione: New. Codice articolo I-9786630447385
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A Deep Learning Approach for Recognition Systems (Paperback)
Print on DemandDa: Grand Eagle Retail, Bensenville, IL, U.S.A.
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Paperback. Condizione: new. Paperback. Biometrics is emerging as one of the most reliable solutions for identifying individuals in modern security systems. Unlike passwords, it relies on physiological characteristics unique to each person, offering a higher level of security.This book focuses on two promising modalities: finger veins and palm prints. While stable and difficult to forge, they remain sensitive to variations in lighting and the quality of the captured images. An approach combining deep learning and machine learning is proposed. Features are extracted using pre-trained convolutional neural networks (VGG16, VGG19, MobileNetV2) and then refined through \textit{fine-tuning}. SVM, KNN, and Random Forest classifiers are then applied, with a comparison between single-instance and multi-instance approaches. MobileNetV2 offers the best performance in terms of accuracy and efficiency. The multi-instance approach enhances the system's robustness, while SVM stands out for its recognition accuracy. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9786630447385
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A Deep Learning Approach for Recognition Systems
Da: PBShop.store UK, Fairford, GLOS, Regno Unito
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PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000. Codice articolo L2-9786630447385
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A Deep Learning Approach for Recognition Systems
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Our Knowledge Publishing Aug 2026, 2026
ISBN 10: 6630447387
ISBN 13: 9786630447385
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 60 pp. Englisch. Codice articolo 9786630447385
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A Deep Learning Approach for Recognition Systems (Paperback)
Print on DemandDa: CitiRetail, Stevenage, Regno Unito
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Paperback. Condizione: new. Paperback. Biometrics is emerging as one of the most reliable solutions for identifying individuals in modern security systems. Unlike passwords, it relies on physiological characteristics unique to each person, offering a higher level of security.This book focuses on two promising modalities: finger veins and palm prints. While stable and difficult to forge, they remain sensitive to variations in lighting and the quality of the captured images. An approach combining deep learning and machine learning is proposed. Features are extracted using pre-trained convolutional neural networks (VGG16, VGG19, MobileNetV2) and then refined through \textit{fine-tuning}. SVM, KNN, and Random Forest classifiers are then applied, with a comparison between single-instance and multi-instance approaches. MobileNetV2 offers the best performance in terms of accuracy and efficiency. The multi-instance approach enhances the system's robustness, while SVM stands out for its recognition accuracy. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Codice articolo 9786630447385
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A Deep Learning Approach for Recognition Systems
Editore:
Our Knowledge Publishing, 2026
ISBN 10: 6630447387
ISBN 13: 9786630447385
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Da: preigu, Osnabrück, Germania
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Taschenbuch. Condizione: Neu. A Deep Learning Approach for Recognition Systems | Cheyma Nadir | Taschenbuch | Englisch | 2026 | Our Knowledge Publishing | EAN 9786630447385 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. Codice articolo 136372655
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A Deep Learning Approach for Recognition Systems
Editore:
Our Knowledge Publishing, 2026
ISBN 10: 6630447387
ISBN 13: 9786630447385
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Taschenbuch
Da: AHA-BUCH GmbH, Einbeck, Germania
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Biometrics is emerging as one of the most reliable solutions for identifying individuals in modern security systems. Unlike passwords, it relies on physiological characteristics unique to each person, offering a higher level of security.This book focuses on two promising modalities: finger veins and palm prints. While stable and difficult to forge, they remain sensitive to variations in lighting and the quality of the captured images. An approach combining deep learning and machine learning is proposed. Features are extracted using pre-trained convolutional neural networks (VGG16, VGG19, MobileNetV2) and then refined through extit{fine-tuning}. SVM, KNN, and Random Forest classifiers are then applied, with a comparison between single-instance and multi-instance approaches. MobileNetV2 offers the best performance in terms of accuracy and efficiency. The multi-instance approach enhances the system's robustness, while SVM stands out for its recognition accuracy. Codice articolo 9786630447385
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