9783659802713 - Mental Health Prediction Using Sentiment Analysis & Facial Recognition de Roy, Abhishek; Sengupta, Souvik; Nayak, Aswani Kumar (11 resultados)

Condición: New.

Condición: New.

Taschenbuch. Condición: Neu. Mental Health Prediction Using Sentiment Analysis & Facial Recognition | Abhishek Roy (u. a.) | Taschenbuch | Englisch | 2025 | LAP LAMBERT Academic Publishing | EAN 9783659802713 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.

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

PAP. Condición: 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. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Mental health disorders represent a growing concern in contemporary society, often remaining undiagnosed due to the subtlety of their symptoms and the stigma surrounding psychological conditions. This project, titled Mental Health Prediction Using Natural Language Sentiment and Facial Expression Recognition, presents a comprehensive, automated framework that leverages advancements in natural language processing and computer vision to identify potential indicators of mental health disturbances. The proposed system adopts a dual-modality approach by analysing both textual data and facial expressions to assess emotional and psychological states. Sentiment analysis is performed on user-generated textual input, extracting emotional cues and evaluating the polarity and intensity of sentiments expressed. Simultaneously, facial expression recognition is employed to decode non-verbal signals using facial landmarks and emotion classification models. By integrating insights from these two modalities, the system enhances the reliability & depth of mental health assessment. This methodology aims to assist mental health professionals by providing a non-invasive, real-time, and scalable solution. 116 pp. Englisch.

Paperback. Condición: new. Paperback. Mental health disorders represent a growing concern in contemporary society, often remaining undiagnosed due to the subtlety of their symptoms and the stigma surrounding psychological conditions. This project, titled Mental Health Prediction Using Natural Language Sentiment and Facial Expression Recognition, presents a comprehensive, automated framework that leverages advancements in natural language processing and computer vision to identify potential indicators of mental health disturbances. The proposed system adopts a dual-modality approach by analysing both textual data and facial expressions to assess emotional and psychological states. Sentiment analysis is performed on user-generated textual input, extracting emotional cues and evaluating the polarity and intensity of sentiments expressed. Simultaneously, facial expression recognition is employed to decode non-verbal signals using facial landmarks and emotion classification models. By integrating insights from these two modalities, the system enhances the reliability & depth of mental health assessment. This methodology aims to assist mental health professionals by providing a non-invasive, real-time, and scalable solution. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Condición: New. Print on Demand.

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 116 pp. Englisch.

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Mental health disorders represent a growing concern in contemporary society, often remaining undiagnosed due to the subtlety of their symptoms and the stigma surrounding psychological conditions. This project, titled Mental Health Prediction Using Natural Language Sentiment and Facial Expression Recognition, presents a comprehensive, automated framework that leverages advancements in natural language processing and computer vision to identify potential indicators of mental health disturbances. The proposed system adopts a dual-modality approach by analysing both textual data and facial expressions to assess emotional and psychological states. Sentiment analysis is performed on user-generated textual input, extracting emotional cues and evaluating the polarity and intensity of sentiments expressed. Simultaneously, facial expression recognition is employed to decode non-verbal signals using facial landmarks and emotion classification models. By integrating insights from these two modalities, the system enhances the reliability & depth of mental health assessment. This methodology aims to assist mental health professionals by providing a non-invasive, real-time, and scalable solution.

Condición: New. PRINT ON DEMAND.