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Purpose - This study analyzes the classification performance and computational efficiency of five pretrained Convolutional Neural Network (CNN) architectures for identifying South Kalimantan traditional food images as an expanded benchmark. Design/methods/approach - The models were trained on a curated traditional food...
Smartphone cameras enable continuous, equipment-free heart rate monitoring, yet the photoplethysmography (PPG) signals they capture are susceptible to movement, contact instability, and environmental variation that differ sharply from controlled validation settings. This study evaluated heart rate estimation from smart...
It is demonstrated that integrating image augmentation and class weighting within the ResNet50-CBAM framework effectively mitigates class imbalance and improves the reliability of automated pneumonia classification.
It is demonstrated that semantic representations and controlled lexical variation can jointly enhance minority-class recognition in short informal Indonesian text and highlight the importance of aligning embedding strategies with sequence architectures.
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