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Arulprakash Enoch (60 results)
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Enhancing The Explainability of Neural Network
Language: English
Published by LAP LAMBERT Academic Publishing, 2024
ISBN 10: 6208064341 ISBN 13: 9786208064341
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
Seller rating 5 out of 5 stars
US$ 89.66
US$ 5.60 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketPAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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Enhancing The Explainability of Neural Network: In the aspects of feature importance, domain rules and algorithmic transparency
Language: English
Published by LAP LAMBERT Academic Publishing, 2024
ISBN 10: 6208064341 ISBN 13: 9786208064341
Condition: New.
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Enhancing The Explainability of Neural Network: In the aspects of feature importance, domain rules and algorithmic transparency
Language: English
Published by LAP LAMBERT Academic Publishing, 2024
ISBN 10: 6208064341 ISBN 13: 9786208064341
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 88.49
US$ 16.11 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
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Enhancing The Explainability of Neural Network: In the aspects of feature importance, domain rules and algorithmic transparency
Language: English
Published by LAP LAMBERT Academic Publishing, 2024
ISBN 10: 6208064341 ISBN 13: 9786208064341
Condition: New.
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Enhancing The Explainability of Neural Network | In the aspects of feature importance, domain rules and algorithmic transparency
Language: English
Published by LAP LAMBERT Academic Publishing, 2024
ISBN 10: 6208064341 ISBN 13: 9786208064341
Taschenbuch. Condition: Neu. Enhancing The Explainability of Neural Network | In the aspects of feature importance, domain rules and algorithmic transparency | Enoch Arulprakash (u. a.) | Taschenbuch | Englisch | 2024 | LAP LAMBERT Academic Publishing | EAN 9786208064341 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.
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Améliorer l'explicabilité des réseaux neuronaux: En ce qui concerne l'importance des caractéristiques, les règles du domaine et la transparence algorithmique (French Edition)
Language: French
Published by Editions Notre Savoir, 2025
ISBN 10: 6202371145 ISBN 13: 9786202371148
Condition: New.
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Améliorer l'explicabilité des réseaux neuronaux | En ce qui concerne l'importance des caractéristiques, les règles du domaine et la transparence algorithmique
Language: French
Published by Editions Notre Savoir, 2025
ISBN 10: 6202371145 ISBN 13: 9786202371148
Taschenbuch. Condition: Neu. Améliorer l'explicabilité des réseaux neuronaux | En ce qui concerne l'importance des caractéristiques, les règles du domaine et la transparence algorithmique | Enoch Arulprakash (u. a.) | Taschenbuch | Französisch | 2025 | Editions Notre Savoir | EAN 9786202371148 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.
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Melhorar a explicabilidade da rede neural
Language: Portuguese
Published by Edi??es Nosso Conhecimento, 2025
ISBN 10: 620237117X ISBN 13: 9786202371179
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
Seller rating 5 out of 5 stars
US$ 94.12
US$ 4.43 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketPAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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Migliorare la spiegabilit? delle reti neurali
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
Seller rating 5 out of 5 stars
US$ 94.12
US$ 4.43 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketPAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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Verbesserung der Erkl?rbarkeit von neuronalen Netzen
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
Seller rating 5 out of 5 stars
US$ 94.12
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Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketPAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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Zwiekszanie zrozumialosci sieci neuronowych
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
Seller rating 5 out of 5 stars
US$ 94.12
US$ 4.43 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketPAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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Melhorar a explicabilidade da rede neural: Nos aspectos da importância das caraterísticas, das regras do domínio e da transparência algorítmica (Portuguese Edition)
Language: Portuguese
Published by Edições Nosso Conhecimento, 2025
ISBN 10: 620237117X ISBN 13: 9786202371179
Condition: New.
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Condition: New.
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Taschenbuch. Condition: Neu. Migliorare la spiegabilità delle reti neurali | Per quanto riguarda l'importanza delle caratteristiche, le regole di dominio e la trasparenza algoritmica | Enoch Arulprakash (u. a.) | Taschenbuch | Italienisch | 2025 | Edizioni Sapienza | EAN 9786202371155 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.
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Melhorar a explicabilidade da rede neural | Nos aspectos da importância das caraterísticas, das regras do domínio e da transparência algorítmica
Language: Portuguese
Published by Edições Nosso Conhecimento, 2025
ISBN 10: 620237117X ISBN 13: 9786202371179
Taschenbuch. Condition: Neu. Melhorar a explicabilidade da rede neural | Nos aspectos da importância das caraterísticas, das regras do domínio e da transparência algorítmica | Enoch Arulprakash (u. a.) | Taschenbuch | Portugiesisch | 2025 | Edições Nosso Conhecimento | EAN 9786202371179 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.
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Taschenbuch. Condition: Neu. Zwi¿kszanie zrozumia¿o¿ci sieci neuronowych | Pod wzgl¿dem wa¿no¿ci funkcji, regu¿ domeny i przejrzysto¿ci algorytmu | Enoch Arulprakash (u. a.) | Taschenbuch | Polnisch | 2025 | Edizioni Sapienza | EAN 9786202371162 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.
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Taschenbuch. Condition: Neu. Verbesserung der Erklärbarkeit von neuronalen Netzen | In Bezug auf die Wichtigkeit der Merkmale, die Regeln des Bereichs und die Transparenz der Algorithmen | Enoch Arulprakash (u. a.) | Taschenbuch | 136 S. | Deutsch | 2025 | Verlag Unser Wissen | EAN 9786202371124 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.
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Condition: Hervorragend. Zustand: Hervorragend | Produktart: Bücher | Künstliche Intelligenz (KI), die von neuronalen Netzen gesteuert wird, ist für viele Anwendungen wie Empfehlungssysteme, Sprachübersetzung, soziale Medien, Chatbots und Rechtschreibprüfung usw. von entscheidender Bedeutung. Diese Netze werden jedoch häufig als "Blackboxen" kritisiert, was Bedenken hinsichtlich ihrer Erklärbarkeit aufkommen lässt, insbesondere in sensiblen Bereichen wie dem Gesundheitswesen, dem autonomen Fahren usw. Bestehende Methoden zur Verbesserung der Erklärbarkeit, wie z. B. die Bedeutung von Merkmalen, sind oft nicht klar und leicht zu interpretieren. Um dieses Problem zu lösen, wurde das objektorientierte neuronale Netz zur Verbesserung der Erklärbarkeit (OONNIE) entwickelt. OONNIE verwendet objektorientierte Modellierung, um Verlust- und Verbindungsgewicht zur Berechnung der Merkmalsbedeutung zu kombinieren und integriert domänenspezifische Regeln durch die Erweiterbarkeit von OOP. Das Modell betont die algorithmische Transparenz, indem jeder Trainingsschritt detailliert beschrieben wird. Bei der Evaluierung von XOR- und XNOR-Funktionen zeigt OONNIE vielversprechende Ergebnisse bei der Merkmalsbedeutung, eine schnellere Verlustreduzierung und verbesserte Vorhersagen nach der Integration von Domänenregeln. Dies ist ein wichtiger Beitrag zur erklärbaren KI und macht OONNIE zu einem wertvollen Werkzeug für die Entwicklung vertrauenswürdiger KI-Systeme.
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Enhancing The Explainability of Neural Network
Language: English
Published by LAP LAMBERT Academic Publishing Sep 2024, 2024
ISBN 10: 6208064341 ISBN 13: 9786208064341
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 204 pp. Englisch.
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Enhancing The Explainability of Neural Network: In the aspects of feature importance, domain rules and algorithmic transparency
Language: English
Published by LAP LAMBERT Academic Publishing, 2024
ISBN 10: 6208064341 ISBN 13: 9786208064341
US$ 125.15
US$ 8.74 shipping
Ships from United Kingdom to U.S.A.Quantity: 4 available
Add to basketCondition: New. Print on Demand.
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Enhancing The Explainability of Neural Network: In the aspects of feature importance, domain rules and algorithmic transparency
Language: English
Published by LAP LAMBERT Academic Publishing, 2024
ISBN 10: 6208064341 ISBN 13: 9786208064341
Condition: New. PRINT ON DEMAND.
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Enhancing The Explainability of Neural Network
Language: English
Published by LAP LAMBERT Academic Publishing Sep 2024, 2024
ISBN 10: 6208064341 ISBN 13: 9786208064341
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Artificial Intelligence (AI) driven by neural networks is crucial in many applications like recommendation systems, language translation, social media, chatbots, and spell-checking etc. However, these networks are often criticized for being 'black boxes,' raising concerns about their explainability, especially in sensitive domains like healthcare, autonomous driving etc. Existing methods to enhance explainability, such as feature importance, often lack clarity and interpretability.To address this, the Object-Oriented Neural Network for Improved Explainability (OONNIE) was developed. OONNIE uses object-oriented modeling to combine loss and connection weight for computing feature importance and integrates domain-specific rules through OOP's extendability. The model emphasizes algorithmic transparency by detailing every training step. Evaluated on XOR and XNOR functions, OONNIE shows promising results in feature importance, faster loss reduction, and improved predictions after integrating domain rules. This marks a significant contribution to explainable AI, making OONNIE a valuable tool for developing trustworthy AI systems.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 204 pp. Englisch.
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Enhancing The Explainability of Neural Network : In the aspects of feature importance, domain rules and algorithmic transparency
Language: English
Published by LAP LAMBERT Academic Publishing, 2024
ISBN 10: 6208064341 ISBN 13: 9786208064341
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering.
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Mejorar la explicabilidad de las redes neuronales
Language: Spanish
Published by Ediciones Nuestro Conocimiento Aug 2025, 2025
ISBN 10: 6202371137 ISBN 13: 9786202371131
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 136 pp. Spanisch.
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Mejorar la explicabilidad de las redes neuronales
Language: Spanish
Published by Ediciones Nuestro Conocimiento Aug 2025, 2025
ISBN 10: 6202371137 ISBN 13: 9786202371131
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -La Inteligencia Artificial (IA) impulsada por redes neuronales es crucial en muchas aplicaciones como los sistemas de recomendación, la traducción de idiomas, las redes sociales, los chatbots, la corrección ortográfica, etc. Sin embargo, a menudo se critica a estas redes por ser 'cajas negras', lo que suscita dudas sobre su explicabilidad, especialmente en ámbitos sensibles como la sanidad, la conducción autónoma, etc. Los métodos existentes para mejorar la explicabilidad, como la importancia de las características, suelen carecer de claridad e interpretabilidad. Para solucionar este problema, se ha desarrollado la red neuronal orientada a objetos para mejorar la explicabilidad (OONNIE). OONNIE utiliza el modelado orientado a objetos para combinar la pérdida y el peso de la conexión para calcular la importancia de las características e integra reglas específicas del dominio gracias a la capacidad de ampliación de la programación orientada a objetos. El modelo enfatiza la transparencia algorítmica detallando cada paso del entrenamiento. Evaluado con funciones XOR y XNOR, OONNIE muestra resultados prometedores en la importancia de las características, una reducción más rápida de las pérdidas y una mejora de las predicciones tras integrar reglas de dominio. Esto supone una importante contribución a la IA explicable, lo que convierte a OONNIE en una valiosa herramienta para desarrollar sistemas de IA fiables.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 136 pp. Spanisch.
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Mejorar la explicabilidad de las redes neuronales : En los aspectos de importancia de las características, reglas de dominio y transparencia algorítmica
Language: Spanish
Published by Ediciones Nuestro Conocimiento, 2025
ISBN 10: 6202371137 ISBN 13: 9786202371131
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering.
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Améliorer l'explicabilité des réseaux neuronaux
Language: French
Published by Editions Notre Savoir Aug 2025, 2025
ISBN 10: 6202371145 ISBN 13: 9786202371148
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 136 pp. Französisch.
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Améliorer l'explicabilité des réseaux neuronaux
Language: French
Published by Editions Notre Savoir Aug 2025, 2025
ISBN 10: 6202371145 ISBN 13: 9786202371148
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -L'intelligence artificielle (IA) pilotée par des réseaux neuronaux est cruciale dans de nombreuses applications telles que les systèmes de recommandation, la traduction linguistique, les médias sociaux, les chatbots, les correcteurs orthographiques, etc. Cependant, ces réseaux sont souvent critiqués pour être des 'boîtes noires', ce qui soulève des inquiétudes quant à leur explicabilité, en particulier dans des domaines sensibles tels que les soins de santé, la conduite autonome, etc. Les méthodes existantes pour améliorer l'explicabilité, telles que l'importance des caractéristiques, manquent souvent de clarté et d'interprétabilité. Pour remédier à ce problème, le réseau neuronal orienté objet pour une meilleure explicabilité (OONNIE) a été mis au point. OONNIE utilise la modélisation orientée objet pour combiner la perte et le poids de connexion afin de calculer l'importance des caractéristiques et intègre des règles spécifiques au domaine grâce à l'extensibilité de la POO. Le modèle met l'accent sur la transparence algorithmique en détaillant chaque étape de la formation. Évalué sur les fonctions XOR et XNOR, OONNIE montre des résultats prometteurs en termes d'importance des caractéristiques, de réduction plus rapide des pertes et d'amélioration des prédictions après l'intégration des règles du domaine. Il s'agit d'une contribution significative à l'IA explicable, qui fait d'OONNIE un outil précieux pour le développement de systèmes d'IA fiables.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 136 pp. Französisch.
