Search for dissertations about: "deep regression"

Showing result 1 - 5 of 44 swedish dissertations containing the words deep regression.

  2. 1. Towards Accurate and Reliable Deep Regression Models

    Author : Fredrik K. Gustafsson; Thomas B. Schön; Martin Danelljan; Søren Hauberg; Uppsala universitet; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Machine Learning; Deep Learning; Regression; Probabilistic Models; Energy-Based Models; Uncertainty Estimation; Machine learning; Maskininlärning;

    Abstract : Regression is a fundamental machine learning task with many important applications within computer vision and other domains. In general, it entails predicting continuous targets from given inputs. READ MORE

  4. 2. Deep Regression and Segmentation for Medical Inference from Large-Scale Magnetic Resonance Imaging

    Author : Taro Langner; Joel Kullberg; Anders Eklund; Uppsala universitet; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Magnetic resonance imaging; medical image analysis; neural networks; machine learning; semantic segmentation; deep regression; saliency analysis; uncertainty quantification; UK Biobank; Medical Informatics; Medicinsk informatik;

    Abstract : Large-scale studies, such as UK Biobank, acquire medical imaging data for thousands of participants. With magnetic resonance imaging (MRI), comprehensive representations of human anatomy can be provided for non-invasive assessments of health-related conditions, body composition, organ volumes, and more. READ MORE

  5. 3. Application of machine learning in systems biology

    Author : Gang Li; Chalmers tekniska högskola; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; uncertainty; Machine learning; genome-scale modelling; deep transfer learning; systems biology; regression;

    Abstract : Biological systems are composed of a large number of molecular components. Understanding their behavior as a result of the interactions between the individual components is one of the aims of systems biology. READ MORE

  6. 4. Evolving intelligence : Overcoming challenges for Evolutionary Deep Learning

    Author : Mohammed Ghaith Altarabichi; Sławomir Nowaczyk; Sepideh Pashami; Peyman Sheikholharam Mashhadi; Niklas Lavesson; Högskolan i Halmstad; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; neural networks; evolutionary deep learning; evolutionary machine learning; feature selection; hyperparameter optimization; evolutionary computation; particle swarm optimization; genetic algorithm;

    Abstract : Deep Learning (DL) has achieved remarkable results in both academic and industrial fields over the last few years. However, DL models are often hard to design and require proper selection of features and tuning of hyper-parameters to achieve high performance. These selections are tedious for human experts and require substantial time and resources. READ MORE

  7. 5. Perspectives of Deep Learning for Neonatal Sepsis Detection

    Author : Antoine Honoré; Saikat Chatterjee; Eric Herlenius; Guy Carrault; KTH; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Deep Learning; Neonatal Sepsis Detection; Normalizing Flows; Hidden Markov Models.; Djupinlärningsmodeller; Neonatal Sepsis detektion; Normaliserande Flöden; Dolda Markov modellerna.;

    Abstract : Newborns, whether born at term or preterm, are highly vulnerable and face life-threatening situations during their initial weeks of life every year. Even with hospitalization in a neonatal intensive care unit (NICU) and careful clinical monitoring, identifying infection-related incidents like sepsis is a challenging task. READ MORE