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A commentary on “Decision Making in Sports” by Johnson (2025)
No full textA commentary on “Decision Making in Sports” by Johnson (2025
Multiagent reinforcement learning in enhancing resilience of microgrids under extreme weather events
No full textMultiagent reinforcement learning in enhancing resilience of microgrids under extreme weather event
Understanding the diverse challenges faced by Australian students studying abroad in the Indo-Pacific
No full textUnderstanding the diverse challenges faced by Australian students studying abroad in the Indo-Pacifi
Challenges and tensions in study-abroad programs for Australian students in the Indo-Pacific
No full textChallenges and tensions in study-abroad programs for Australian students in the Indo-Pacifi
Multiclass Semantic Segmentation of Satellite Imagery Using Convolutional Neural Networks
No full textMulticlass Semantic Segmentation of Satellite Imagery Using Convolutional Neural Network
Scalar projective synchronization for uncertain T-S fuzzy systems with unified control fluctuation: Implementation to quadruple-tank process model
No full textScalar projective synchronization for uncertain T-S fuzzy systems with unified control fluctuation: Implementation to quadruple-tank process mode
Sub-synchronous oscillations in power systems with high renewable integration: Analytical models, mitigation strategies, and emerging challenges
No full textSub-synchronous oscillations in power systems with high renewable integration: Analytical models, mitigation strategies, and emerging challenges</p
Macro-expression-guided micro-expression recognition: A motion similarity perspective
No full textMicro-expression recognition (MER) is a challenging task due to the subtle and short-lived facial muscle movements involved. Macro-expressions, in contrast, are more evident and easy to recognize. Yet, both expressions share similar facial muscles to express the same emotions. We exploit this observation to propose a novel Macro-expression guidance network (MAG) that uses motion similarity to aid MER. The MAG has four key components: 1) motion vectorization, which transforms facial motion into a vector tensor representation to capture motion dynamics; 2) nonlinear amplification, which enhances the intensity of micro-expression features to make them more salient; 3) macro-micro matching, which aligns macro- and micro-expressions with the highest motion similarity to achieve a one-to-one mapping between the two modalities; and 4) guidance mechanism, which enables macro-expressions to guide the extraction of micro-expression features using convolutional operations. We perform extensive experiments on 7 datasets under 3 benchmarks and demonstrate that MAG outperforms state-of-the-art methods for MER
Valuation of EQ-5D Health States for Adults in Low-, Lower-Middle, and Upper-Middle-Income Countries: A Systematic Review
No full textValuation of EQ-5D Health States for Adults in Low-, Lower-Middle, and Upper-Middle-Income Countries: A Systematic Revie
Seasonal, compositional, and meteorological drivers of PM2.5 oxidative potential: Evidence from a year-long multi-assay study in Melbourne
No full textSeasonal, compositional, and meteorological drivers of PM2.5 oxidative potential: Evidence from a year-long multi-assay study in Melbourn