2026-04-17T05:10:27Zhttps://recercat.cat/oai/request

oai:recercat.cat:2117/4450452025-11-01T18:31:53Zcom_2072_1033col_2072_452951

00925njm 22002777a 4500 dc Sztamborski, Adam author 2025-10-22 Image segmentation is a fundamental task in image processing, with applications ranging from medical imaging to autonomous systems. This thesis introduces a novel Deep Discriminant Analysis (DDA) loss, which integrates classical discriminant analysis principles into deep neural networks to increase class separability in segmentation tasks. The proposed loss encourages the network to produce wellseparated representations of foreground and background pixels in the learned feature space, leading to more discriminative and interpretable representations. The effectiveness of the DDA loss is first validated on synthetic and simple classi-cation problems, then evaluated on the challenging DIS5K dataset using a tailored U-Net architecture. Experimental results demonstrate consistent improvements over the standard Binary Cross-Entropy (BCE) loss, yielding faster convergence, higher separability, and superior segmentation metrics across multiple test subsets. All experiments are carried out using publicly available datasets and open-source frameworks, with careful consideration of reproducibility, computational efficiency, and ethical standards. These findings confirm that discriminant analysis principles can be effectively embedded within deep architectures, offering a practical enhancement to contemporary segmentation methods. http://hdl.handle.net/2117/445045 Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic Computer vision Deep learning Machine learning Imaging systems in medicine Deep Discriminant Analysis Discriminant loss Fisher criterion Image segmentation U-Net Convolutional neural networks Deep learning Dichotomous image segmentation Anàlisi discriminant profunda Pèrdua discriminant Criteri de Fisher Segmentació d'imatges Aprenentatge profund Segmentació dicotòmica d'imatges Segmentació dicotòmica d'imatges Visió per ordinador Aprenentatge profund Aprenentatge automàtic Imatgeria mèdica Deep Discriminant Analysis in binary segmentation of images