"The wristGuard application employs a hybrid approach, combining deep learning models for feature extraction and stacking ensemble method for classification of wrist fracture types.This algorithm combines deep learning-based feature extraction with a stacking ensemble classification approach to improve wrist fracture detection. It utilizes four pre-trained CNNs, namely MobileNet, ResNet50, DenseNet121, and InceptionV3, to extract high-level features from grayscale X-ray images, which are then used by XGBoost classifiers for fracture classification. "
Security and cryptocurrency wallet use are still at the center of the issues with blockchain adoption. Seed phrase-based physical wallets…
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“The wristGuard application employs a hybrid approach, combining deep learning models for feature extraction and stacking ensemble method for classification…
“The COVID-19 epidemic changed IT industry processes by hastening the introduction of remote work. In virtual workplaces, detecting employee engagement…
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