TY  - EJOU
AU  - Talib, Hafiz Khizer bin 
AU  - Cao, Yanlong 
AU  - Zaman, Muhammad 
AU  - Ahmad, Sharifah Sakinah Syed 
AU  - Ivkovic, Nikola 
AU  - Konecki, Mario 
AU  - Akhunzada, Adnan 

TI  - BroadAttNet: Attention-Driven Micro-Expression Recognition
T2  - Computers, Materials \& Continua

PY  - 
VL  - 
IS  - 
SN  - 1546-2226

AB  - Micro-expression recognition (MER) is a demanding problem in affective computing because micro-expressions are brief, low-amplitude, involuntary facial movements that often reveal concealed affective states. Their recognition is complicated by weak muscle activation, short temporal duration, inter-subject variability, class imbalance, illumination changes, and the limited scale of publicly available MER datasets. To address these constraints, this paper introduces BroadAttNet, an attention-driven convolutional framework that embeds a Broadbent-inspired selective attention layer into a compact CNN backbone. The proposed layer learns to assign higher importance to discriminative facial regions while suppressing spatially redundant or noisy responses, thereby improving feature selectivity, interpretability, and recognition robustness without imposing substantial computational overhead. BroadAttNet is evaluated on three benchmark micro-expression datasets, SAMM, CASME II, and SMIC, using both K-Fold and Stratified K-Fold cross-validation protocols. The model achieves accuracies of 99.66% and 99.73% on SAMM, 98.73% and 97.65% on CASME II, and 98.62% and 97.09% on SMIC under K-Fold and Stratified K-Fold validation, respectively. Complementary ablation analysis, per-class evaluation, UAR reporting, model complexity analysis, and Grad-CAM visualization further demonstrate that the Broadbent Attention layer improves discriminative representation while preserving efficient inference. These findings indicate that BroadAttNet provides a robust, interpretable, and computationally practical solution for MER in human-computer interaction, behavioral analysis, and emotion-aware intelligent systems.
KW  - BroadAttNet; broadbent attention mechanism; micro-expression recognition; convolutional neural network; explainable affective computing; stratified K-Fold cross-validation; SAMM; CASME II; SMIC

DO  - 10.32604/cmc.2026.078779