Titlebook: Disruptive Information Technologies for a Smart Society; Proceedings of the 1 Miroslav Trajanovi?,Nenad Filipovi?,Milan Zdravkov Conference

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Bridging the Gap: Physics-Driven Deep Learning for Heat Transfer Model of the Heart Tissueearning methods by merging data-driven and physics-driven approaches. PINNs offer advantages in handling computationally and temporally demanding problems that were conventionally approached using techniques like Finite Difference Method (FDM). This study focuses on analyzing heat transfer within ca

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Comparison of Different Convolutional Neural Networks Utilizing Transfer Learning for Pneumothorax Sorax, chest X-ray is a commonly used imaging technique. U-Net convolutional neural network models with different backbones are compared in order to assess their capability to automatically and correctly segment signs of pneumothorax from chest X-rays. Five different pretrained backbones have been ch

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Can Augmented Real-time Haptic Feedback Assist Young Professional Swimmers in Improving Swimming Tecoys a specially designed wearable device with haptic actuators and an integrated orientation sensor. The device measures and stores the maximum body rotation angles during each swim stroke and gives the swimmers real-time feedback on their performance so that they can react, if needed, by changing t

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availability. The reduced computational demands of conventional ML approaches not only result in cost savings but also minimize the carbon footprint associated with data analysis tasks in energy systems.