3 papers
cs.CV2026
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…
cs.CV2026
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…
cs.CV2024
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…