P Narasimhaiah (54 results)

Condition: New.

Condition: New.

Taschenbuch. Condition: Neu. Early Detection and Classification of Breast Cancer Using ML | P. Narasimhaiah (u. a.) | Taschenbuch | Englisch | 2026 | LAP LAMBERT Academic Publishing | EAN 9786209575037 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. …

Condition: New.

Taschenbuch. Condition: Neu. Détection précoce et classification du cancer du sein à l'aide de la ML | P. Narasimhaiah (u. a.) | Taschenbuch | Französisch | 2026 | Editions Notre Savoir | EAN 9786209720802 | Verantwortliche Person für die EU: Editions Notre Savoir, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. …

Condition: New.

Condition: New.

Condition: New.

Condition: New.

Condition: New.

Taschenbuch. Condition: Neu. Rilevamento precoce e classificazione del cancro al seno mediante ML | P. Narasimhaiah (u. a.) | Taschenbuch | Italienisch | 2026 | Edizioni Sapienza | EAN 9786209723360 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. …

Taschenbuch. Condition: Neu. Deteção precoce e classificação do cancro da mama utilizando ML | P. Narasimhaiah (u. a.) | Taschenbuch | Portugiesisch | 2026 | Edições Nosso Conhecimento | EAN 9786209731044 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.…

Taschenbuch. Condition: Neu. Wczesne wykrywanie i klasyfikacja raka piersi przy u¿yciu uczenia maszynowego | P. Narasimhaiah (u. a.) | Taschenbuch | Polnisch | 2026 | Wydawnictwo Nasza Wiedza | EAN 9786209725920 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. …

Condition: New.

Taschenbuch. Condition: Neu. Früherkennung und Klassifizierung von Brustkrebs mit ML | P. Narasimhaiah (u. a.) | Taschenbuch | 100 S. | Deutsch | 2026 | Verlag Unser Wissen | EAN 9786209715686 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. …

PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 120 pp. Englisch.

PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Paperback. Condition: new. Paperback. The most common cancer among the women in the world with high mortality rate is breast cancer. Early detection and accurate classification of breast cancer are essential for improving patient survival and enabling timely clinical intervention. Machine learning techniques have been widely applied to analyze diagnostic data from mammography, ultrasound, magnetic resonance imaging, and histopathological examinations. Traditional machine learning methods use handcrafted features classified by algorithms such as Support Vector Machines and Random Forests, while deep learning models, particularly convolutional neural networks, automatically learn discriminative feature representations from raw data. Experimental studies show that these models can effectively distinguish between benign and malignant lesions with high accuracy, supporting radiologists in early-stage diagnosis. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

PAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 100 pp. Spanisch.

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The most common cancer among the women in the world with high mortality rate is breast cancer. Early detection and accurate classification of breast cancer are essential for improving patient survival and enabling timely clinical intervention. Machine learning techniques have been widely applied to analyze diagnostic data from mammography, ultrasound, magnetic resonance imaging, and histopathological examinations. Traditional machine learning methods use handcrafted features classified by algorithms such as Support Vector Machines and Random Forests, while deep learning models, particularly convolutional neural networks, automatically learn discriminative feature representations from raw data. Experimental studies show that these models can effectively distinguish between benign and malignant lesions with high accuracy, supporting radiologists in early-stage diagnosis.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 120 pp. Englisch.…

Condition: New. Print on Demand.

Condition: New. PRINT ON DEMAND.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - El cáncer de mama es el más frecuente entre las mujeres de todo el mundo, con una elevada tasa de mortalidad. La detección precoz y la clasificación precisa del cáncer de mama son esenciales para mejorar la supervivencia de las pacientes y permitir una intervención clínica oportuna. Las técnicas de aprendizaje automático se han aplicado ampliamente para analizar datos de diagnóstico procedentes de mamografías, ecografías, resonancias magnéticas y exámenes histopatológicos. Los métodos tradicionales de aprendizaje automático utilizan características artesanales clasificadas por algoritmos como Support Vector Machines y Random Forests, mientras que los modelos de aprendizaje profundo, en particular las redes neuronales convolucionales, aprenden automáticamente representaciones de características discriminativas a partir de datos brutos. Los estudios experimentales demuestran que estos modelos pueden distinguir eficazmente entre lesiones benignas y malignas con gran precisión, lo que ayuda a los radiólogos en el diagnóstico precoz.…

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Le cancer du sein est le cancer le plus fréquent chez les femmes dans le monde, avec un taux de mortalité élevé. La détection précoce et la classification précise du cancer du sein sont essentielles pour améliorer la survie des patientes et permettre une intervention clinique opportune. Les techniques d'apprentissage automatique ont été largement appliquées à l'analyse des données diagnostiques provenant de la mammographie, de l'échographie, de l'imagerie par résonance magnétique et des examens histopathologiques. Les méthodes traditionnelles d'apprentissage automatique utilisent des caractéristiques artisanales classées par des algorithmes tels que les machines à vecteurs de support et les forêts aléatoires, tandis que les modèles d'apprentissage profond, en particulier les réseaux neuronaux convolutifs, apprennent automatiquement des représentations de caractéristiques discriminantes à partir de données brutes. Des études expérimentales montrent que ces modèles peuvent distinguer efficacement les lésions bénignes et malignes avec une grande précision, aidant ainsi les radiologues à établir un diagnostic précoce. 100 pp. Französisch.…

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -El cáncer de mama es el más frecuente entre las mujeres de todo el mundo, con una elevada tasa de mortalidad. La detección precoz y la clasificación precisa del cáncer de mama son esenciales para mejorar la supervivencia de las pacientes y permitir una intervención clínica oportuna. Las técnicas de aprendizaje automático se han aplicado ampliamente para analizar datos de diagnóstico procedentes de mamografías, ecografías, resonancias magnéticas y exámenes histopatológicos. Los métodos tradicionales de aprendizaje automático utilizan características artesanales clasificadas por algoritmos como Support Vector Machines y Random Forests, mientras que los modelos de aprendizaje profundo, en particular las redes neuronales convolucionales, aprenden automáticamente representaciones de características discriminativas a partir de datos brutos. Los estudios experimentales demuestran que estos modelos pueden distinguir eficazmente entre lesiones benignas y malignas con gran precisión, lo que ayuda a los radiólogos en el diagnóstico precoz.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 100 pp. Spanisch.…

PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.