Isbn: 9786208436063 - deep learning for emotion recognition: from theory to practice: leveraging contextual and multimodal approaches for enhanced understanding (10 risultati)

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Condizione: New.

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Taschenbuch. Condizione: Neu. Deep Learning for Emotion Recognition: From Theory to Practice | Leveraging Contextual and Multimodal Approaches for Enhanced Understanding | Fatiha Limami | Taschenbuch | Englisch | 2025 | LAP LAMBERT Academic Publishing | EAN 9786208436063 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.…

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book investigates developments in computer vision and artificial intelligence automated emotional perception. Specifically, we use deep learning, DCNN, and VGG19 algorithms to combine body language and contextual information, including environmental, social, and cultural factors. We optimize deep neural networks by aggregating many picture datasets, including EMOTIC (ADE20K, MSCOCO), EMODB_SMALL, and FRAMESDB, to evaluate continuous emotional dimensions and discrete emotions properly. Our results show notable progress over current methods, improving contextual emotional awareness. This work opens the path for significant applications in social robotics, affective computing, and human-machine interaction, enabling complex emotional sensing in many different real-world contexts. 52 pp. Englisch.…

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book investigates developments in computer vision and artificial intelligence automated emotional perception. Specifically, we use deep learning, DCNN, and VGG19 algorithms to combine body language and contextual information, including environmental, social, and cultural factors. We optimize deep neural networks by aggregating many picture datasets, including EMOTIC (ADE20K, MSCOCO), EMODB_SMALL, and FRAMESDB, to evaluate continuous emotional dimensions and discrete emotions properly. Our results show notable progress over current methods, improving contextual emotional awareness. This work opens the path for significant applications in social robotics, affective computing, and human-machine interaction, enabling complex emotional sensing in many different real-world contexts.…

Condizione: New. Print on Demand.

Condizione: New. Print on Demand.

Condizione: New. PRINT ON DEMAND.

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book investigates developments in computer vision and artificial intelligence automated emotional perception. Specifically, we use deep learning, DCNN, and VGG19 algorithms to combine body language and contextual information, including environmental, social, and cultural factors. We optimize deep neural networks by aggregating many picture datasets, including EMOTIC (ADE20K, MSCOCO), EMODB_SMALL, and FRAMESDB, to evaluate continuous emotional dimensions and discrete emotions properly. Our results show notable progress over current methods, improving contextual emotional awareness. This work opens the path for significant applications in social robotics, affective computing, and human-machine interaction, enabling complex emotional sensing in many different real-world contexts.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 52 pp. Englisch.…