Sökning: "Statistical image and signal processing"
Visar resultat 1 - 5 av 29 avhandlingar innehållade orden Statistical image and signal processing.
1. Time-domain Reconstruction Methods for Ultrasonic Array Imaging : A Statistical Approach
Sammanfattning : This thesis is concerned with reconstruction techniques for ultrasonic array imaging based on a statistical approach. The reconstruction problem is posed as the estimation of an image consisting of scattering strengths. LÄS MER
2. Group-Sparse Regression : With Applications in Spectral Analysis and Audio Signal Processing
Sammanfattning : This doctorate thesis focuses on sparse regression, a statistical modeling tool for selecting valuable predictors in underdetermined linear models. By imposing different constraints on the structure of the variable vector in the regression problem, one obtains estimates which have sparse supports, i.e. LÄS MER
3. Computerized Cell and Tissue Analysis
Sammanfattning : The latest advances in digital cameras combined with powerful computer software enable us to store high-quality microscopy images of specimen. Studying hundreds of images manually is very time consuming and has the problem of human subjectivity and inconsistency. LÄS MER
4. Quantitative image analysis : a focus on automated characterization of structures in optical microscopy of iron ore pellets
Sammanfattning : Sintering occurs in many types of material such as iron, ceramics and snow, typically during thermal treatment, and aects the material properties, particularly the strength, by the bonding of particles into a coherent structure. In order to improve the mechanical strength in magnetite iron ore pellets it is important to be able to characterize and quantitatively measure the degree of sintering and features that impact the process of sintering. LÄS MER
5. Generalization under Model Mismatch and Distributed Learning
Sammanfattning : Machine learning models are typically configured by minimizing the training error over a given training dataset. On the other hand, the main objective is to obtain models that can generalize, i.e., perform well on data unseen during training. LÄS MER