Efficient Unsupervised Domain Adaptation Regression for Spatial-Temporal Sensor Fusion

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The application of unsupervised domain adaptation (UDA)-based fault diagnosis methods has shown significant efficacy in industrial settings, facilitating the transfer of operational experience and fault signatures between different operating conditions, di ...

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The shear resistance of headed studs is of paramount importance for the design of steel-concrete composite structures and an accurate predictive model is highly needed. Ensemble learning is expected to be a powerful solution while it relies on laborious se ...

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The use of drones in search and rescue (SAR) missions can be very cognitively demanding. Since high levels of cognitive workload can negatively affect human performance, there is a risk of compromising the mission and leading to failure with catastrophic o ...

Efficient Unsupervised Domain Adaptation Regression for Spatial-Temporal Sensor Fusion

Chattez avec Graph Search

Intelligent Soft Robotic System for Sensing and Recognition via Triboelectric‐Based Multi‐Sensor Fusion

Ensemble learning for portfolio valuation and risk management

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Musculoskeletal motor control with reinforcement learning

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Beyond Pixels: Semi-supervised Semantic Segmentation with a Multi-scale Patch-Based Multi-label Classifier

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Learnable Wavelet Transform and Domain Adversarial Learning for Enhanced Bearing Fault Diagnosis

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Auto-tuning ensemble models for estimating shear resistance of headed studs in concrete

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Stochasticity helps to navigate rough landscapes: comparing gradient-descent-based algorithms in the phase retrieval problem

Cognitive workload monitoring in virtual reality based rescue missions with drones