5 papers
End-to-End Image Compression with Segmentation Guided Dual Coding for Wind Turbines
Raül Pérez-Gonzalo, Andreas Espersen, Søren Forchhammer +1
Transferring large volumes of high-resolution images during wind turbine inspections introduces a bottleneck in assessing and detecting severe defects. Efficient coding must preser…
Unsupervised Modular Adaptive Region Growing and RegionMix Classification for Wind Turbine Segmentation
Raül Pérez-Gonzalo, Riccardo Magro, Andreas Espersen +1
Reliable operation of wind turbines requires frequent inspections, as even minor surface damages can degrade aerodynamic performance, reduce energy output, and accelerate blade wea…
Probabilistic Deep Discriminant Analysis for Wind Blade Segmentation
Raül Pérez-Gonzalo, Andreas Espersen, Antonio Agudo
Linear discriminant analysis improves class separability but struggles with non-linearly separable data. To overcome this, we introduce Deep Discriminant Analysis (DDA), which dire…
Discriminant Learning-based Colorspace for Blade Segmentation
Raül Pérez-Gonzalo, Andreas Espersen, Antonio Agudo
Suboptimal color representation often hinders accurate image segmentation, yet many modern algorithms neglect this critical preprocessing step. This work presents a novel multidime…
Dual-Space Augmented Intrinsic-LoRA for Wind Turbine Segmentation
Shubh Singhal, Raül Pérez-Gonzalo, Andreas Espersen +1
Accurate segmentation of wind turbine blade (WTB) images is critical for effective assessments, as it directly influences the performance of automated damage detection systems. Des…