menu
{ "item_title" : "Multimodal Emotion Recognition Using Deep Learning Networks", "item_author" : [" Jaykumar Vala", "Udesang Jaliya "], "item_description" : "This book, Multimodal Emotion Recognition Using Deep Learning Networks focuses on improving emotion recognition by combining multiple data sources (modalities) like facial expressions, EEG, and Physiological signals. Deep learning models are used to extract features from each modality, and fusion techniques (such as late fusion approach) integrate these features to make more accurate emotion predictions. The study shows that multimodal fusion significantly boosts performance over single-modality systems, highlighting the importance of combining complementary emotional cues using advanced neural network architectures.", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/6/20/908/677/6209086772_b.jpg", "price_data" : { "retail_price" : "80.00", "online_price" : "80.00", "our_price" : "80.00", "club_price" : "80.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Multimodal Emotion Recognition Using Deep Learning Networks|Jaykumar Vala

Multimodal Emotion Recognition Using Deep Learning Networks

local_shippingShip to Me
In Stock.
FREE Shipping for Club Members help

Overview

This book, "Multimodal Emotion Recognition Using Deep Learning Networks" focuses on improving emotion recognition by combining multiple data sources (modalities) like facial expressions, EEG, and Physiological signals. Deep learning models are used to extract features from each modality, and fusion techniques (such as late fusion approach) integrate these features to make more accurate emotion predictions. The study shows that multimodal fusion significantly boosts performance over single-modality systems, highlighting the importance of combining complementary emotional cues using advanced neural network architectures.

This item is Non-Returnable

Details

  • ISBN-13: 9786209086779
  • ISBN-10: 6209086772
  • Publisher: LAP Lambert Academic Publishing
  • Publish Date: October 2025
  • Dimensions: 9 x 6 x 0.32 inches
  • Shipping Weight: 0.42 pounds
  • Page Count: 136

Related Categories

You May Also Like...

    1

BAM Customer Reviews