dr arjun kuruva (53 risultati)

Condizione: New.

Condizione: New.

Condizione: New.

Condizione: New.

Condizione: New.

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

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

Paperback. Condizione: new. Paperback. In today's digital world, emotions are conveyed not only through words but also through emojis that enrich and redefine human expression. Hybrid Deep Learning Models for Sentiment Analysis using Text and Emojis presents a groundbreaking approach to understanding sentiments by integrating textual and emoji-based data within advanced deep learning frameworks.This book introduces innovative hybrid architectures-ECSSO, EBERT, and HCGO-that combine the strengths of convolutional, recurrent, transformer, and graph-based neural networks. By fusing linguistic and visual-emotional cues, these models achieve remarkable accuracy in interpreting complex sentiments, sarcasm, and context-rich digital communication.Through comprehensive experiments and evaluations, the research demonstrates significant improvements over traditional text-only systems, highlighting the transformative role of emojis in emotion-aware artificial intelligence.Designed for researchers, scholars, and professionals in Natural Language Processing (NLP), Artificial Intelligence (AI), and Data Science, this book offers deep insights into multimodal sentiment analysis and the future of emotionally intelligent computing. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Paperback. Condizione: new. Paperback. In today's digital world, emotions are conveyed not only through words but also through emojis that enrich and redefine human expression. Hybrid Deep Learning Models for Sentiment Analysis using Text and Emojis presents a groundbreaking approach to understanding sentiments by integrating textual and emoji-based data within advanced deep learning frameworks.This book introduces innovative hybrid architectures-ECSSO, EBERT, and HCGO-that combine the strengths of convolutional, recurrent, transformer, and graph-based neural networks. By fusing linguistic and visual-emotional cues, these models achieve remarkable accuracy in interpreting complex sentiments, sarcasm, and context-rich digital communication.Through comprehensive experiments and evaluations, the research demonstrates significant improvements over traditional text-only systems, highlighting the transformative role of emojis in emotion-aware artificial intelligence.Designed for researchers, scholars, and professionals in Natural Language Processing (NLP), Artificial Intelligence (AI), and Data Science, this book offers deep insights into multimodal sentiment analysis and the future of emotionally intelligent computing. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Paperback. Condizione: new. Paperback. In today's digital world, emotions are conveyed not only through words but also through emojis that enrich and redefine human expression. Hybrid Deep Learning Models for Sentiment Analysis using Text and Emojis presents a groundbreaking approach to understanding sentiments by integrating textual and emoji-based data within advanced deep learning frameworks.This book introduces innovative hybrid architectures-ECSSO, EBERT, and HCGO-that combine the strengths of convolutional, recurrent, transformer, and graph-based neural networks. By fusing linguistic and visual-emotional cues, these models achieve remarkable accuracy in interpreting complex sentiments, sarcasm, and context-rich digital communication.Through comprehensive experiments and evaluations, the research demonstrates significant improvements over traditional text-only systems, highlighting the transformative role of emojis in emotion-aware artificial intelligence.Designed for researchers, scholars, and professionals in Natural Language Processing (NLP), Artificial Intelligence (AI), and Data Science, this book offers deep insights into multimodal sentiment analysis and the future of emotionally intelligent computing. 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.

Condizione: New. Print on Demand.

Condizione: New. Print on Demand.

Condizione: New. PRINT ON DEMAND.

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

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

Paperback. Condizione: new. Paperback. Dans le monde numerique actuel, les emotions s'expriment non seulement par les mots, mais aussi par les emojis, qui enrichissent et redefinissent l'expression humaine. L'ouvrage Hybrid Deep Learning Models for Sentiment Analysis using Text and Emojis presente une approche novatrice de la comprehension des sentiments, integrant donnees textuelles et emojis au sein de frameworks d'apprentissage profond avances. Ce livre introduit des architectures hybrides innovantes - ECSSO, EBERT et HCGO - qui combinent les atouts des reseaux de neurones convolutifs, recurrents, transformeurs et bases sur les graphes. En fusionnant les indices linguistiques et visuels-emotionnels, ces modeles atteignent une precision remarquable dans l'interpretation des sentiments complexes, du sarcasme et des communications numeriques riches en contexte. Grace a des experiences et des evaluations exhaustives, la recherche demontre des ameliorations significatives par rapport aux systemes textuels traditionnels, soulignant le role transformateur des emojis dans l'intelligence artificielle sensible aux emotions. Destine aux chercheurs, universitaires et professionnels du traitement automatique du langage naturel (TALN), de l'intelligence artificielle (IA) et des sciences des donnees, cet ouvrage offre une analyse approfondie de l'analyse multimodale des sentiments et de l'avenir de l'informatique emotionnellement intelligente. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Paperback. Condizione: new. Paperback. Dans le monde numerique actuel, les emotions s'expriment non seulement par les mots, mais aussi par les emojis, qui enrichissent et redefinissent l'expression humaine. L'ouvrage Hybrid Deep Learning Models for Sentiment Analysis using Text and Emojis presente une approche novatrice de la comprehension des sentiments, integrant donnees textuelles et emojis au sein de frameworks d'apprentissage profond avances. Ce livre introduit des architectures hybrides innovantes - ECSSO, EBERT et HCGO - qui combinent les atouts des reseaux de neurones convolutifs, recurrents, transformeurs et bases sur les graphes. En fusionnant les indices linguistiques et visuels-emotionnels, ces modeles atteignent une precision remarquable dans l'interpretation des sentiments complexes, du sarcasme et des communications numeriques riches en contexte. Grace a des experiences et des evaluations exhaustives, la recherche demontre des ameliorations significatives par rapport aux systemes textuels traditionnels, soulignant le role transformateur des emojis dans l'intelligence artificielle sensible aux emotions. Destine aux chercheurs, universitaires et professionnels du traitement automatique du langage naturel (TALN), de l'intelligence artificielle (IA) et des sciences des donnees, cet ouvrage offre une analyse approfondie de l'analyse multimodale des sentiments et de l'avenir de l'informatique emotionnellement intelligente. 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.

Paperback. Condizione: new. Paperback. Dans le monde numerique actuel, les emotions s'expriment non seulement par les mots, mais aussi par les emojis, qui enrichissent et redefinissent l'expression humaine. L'ouvrage Hybrid Deep Learning Models for Sentiment Analysis using Text and Emojis presente une approche novatrice de la comprehension des sentiments, integrant donnees textuelles et emojis au sein de frameworks d'apprentissage profond avances. Ce livre introduit des architectures hybrides innovantes - ECSSO, EBERT et HCGO - qui combinent les atouts des reseaux de neurones convolutifs, recurrents, transformeurs et bases sur les graphes. En fusionnant les indices linguistiques et visuels-emotionnels, ces modeles atteignent une precision remarquable dans l'interpretation des sentiments complexes, du sarcasme et des communications numeriques riches en contexte. Grace a des experiences et des evaluations exhaustives, la recherche demontre des ameliorations significatives par rapport aux systemes textuels traditionnels, soulignant le role transformateur des emojis dans l'intelligence artificielle sensible aux emotions. Destine aux chercheurs, universitaires et professionnels du traitement automatique du langage naturel (TALN), de l'intelligence artificielle (IA) et des sciences des donnees, cet ouvrage offre une analyse approfondie de l'analyse multimodale des sentiments et de l'avenir de l'informatique emotionnellement intelligente. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Condizione: New. Print on Demand.

Condizione: New. Print on Demand.

Condizione: New. PRINT ON DEMAND.

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

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

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

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

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

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

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

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

Paperback. Condizione: new. Paperback. In der heutigen digitalen Welt werden Emotionen nicht nur durch Worte, sondern auch durch Emojis vermittelt, die den menschlichen Ausdruck bereichern und neu definieren. "Hybride Deep-Learning-Modelle fuer die Stimmungsanalyse mit Text und Emojis" praesentiert einen bahnbrechenden Ansatz zum Verstaendnis von Stimmungen durch die Integration text- und emojibasierter Daten in fortschrittliche Deep-Learning-Frameworks. Dieses Buch stellt innovative Hybridarchitekturen vor - ECSSO, EBERT und HCGO -, die die Staerken von Faltungs-, rekurrenten, transformatorischen und graphenbasierten neuronalen Netzen vereinen. Durch die Kombination linguistischer und visuell-emotionaler Signale erreichen diese Modelle eine bemerkenswerte Genauigkeit bei der Interpretation komplexer Stimmungen, Sarkasmus und kontextreicher digitaler Kommunikation. Umfassende Experimente und Evaluierungen belegen signifikante Verbesserungen gegenueber herkoemmlichen, rein textbasierten Systemen und unterstreichen die transformative Rolle von Emojis in der emotionssensitiven kuenstlichen Intelligenz. Dieses Buch richtet sich an Forscher, Wissenschaftler und Fachleute aus den Bereichen Verarbeitung natuerlicher Sprache (NLP), Kuenstliche Intelligenz (KI) und Data Science und bietet tiefe Einblicke in die multimodale Stimmungsanalyse und die Zukunft des emotional intelligenten Computings. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.