BFER-Net: Babies Facial Expression Recognition Model Using ResNet12 Enabled Few-Shot Embedding Adaptation and Convolutional Block Attention Modules

BFER-Net: Babies Facial Expression Recognition Model Using ResNet12 Enabled Few-Shot Embedding Adaptation and Convolutional Block Attention Modules

The recognition of babies’ facial expressions is challenging due to the limited availability of annotated data and the complex nature of their emotions.To address this problem, this work introduces a novel dataset, FER-BYC (Facial Expression Recognition for Bangladeshi Young Children), co...

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Bibliographic Details
Main Authors: Sumiya Arafin, Adnan Ferdous Ashrafi, Md. Golam Rabiul Alam, Ashis Talukder
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Facial emotion recognition (FER)
few-shot learning (FSL)
prototypical networks
convolutional block attention module (CBAM)
babies’ facial emotion
BFER-Net
Online Access:https://ieeexplore.ieee.org/document/10902359/
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https://ieeexplore.ieee.org/document/10902359/

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