Now showing items 1-20 of 24

• #### Active and Transfer learning Methods for Computational Histology ﻿

(2012-12)
Tissue micro-environments of critical interest like tumors, stem-cell niches, and brain tissue surrounding implanted neuroprosthetic devices are complex in structure and harbor complex processes. Understanding events and ...
• #### Binary Frames, Codes and Euclidean Embeddings ﻿

(2018-12)
This dissertation has two parts. The first part is concerned with using Euclidean embeddings and random hyperplane tessellations to construct binary block codes. The construction proceeds in two stages. First, an auxiliary ...
• #### Characterization of the Transition Region in the QCD Phase Diagram ﻿

(2019-05)
The study of the Quantum Chromodynamics (QCD) phase diagram has been the object of great effort in the scientific community both from theory and experiment, and has been investigated from first principles through lattice ...
• #### Compactly Supported Frame Wavelets and Applications ﻿

(2019-08)
Signal processing has been at the forefront of modern information technology as the need for storing, analyzing, and interpreting data gathered all around us is ever growing. Multi-dimensional sparse signal representations ...
• #### DIRECTIONAL MULTISCALE ANALYSIS USING SHEARLET THEORY AND APPLICATIONS ﻿

(2012-08)
Shearlets emerged in recent years in applied harmonic analysis as a general framework to provide sparse representations of multidimensional data. This construction was motivated by the need to provide more efficient ...
• #### Extraction and Normalization of Directional Characteristics of Images and Textures using Multiscale Transforms ﻿

(2014-12)
This dissertation consists of two projects, one of which is on illumination normalization in monochromatic images that form Chapter 1 of this dissertation. The second project is on Texture analysis and application in  cancer ...
• #### FRAMES AS CODES FOR STRUCTURED ERASURES ﻿

(2012-12)
This dissertation studies the role of frames as codes. Frames are families of vectors that give rise to embeddings of Hilbert spaces. These embeddings can be interpreted as codes, because possible linear dependencies among ...
• #### From Generalized Fourier Transforms to Coupled Supersymmetry ﻿

(2017-05)
The Fourier transform, the quantum mechanical harmonic oscillator, and supersymmetric quantum mechanics are well-studied objects in mathematics. The relations between them are also well-understood, though the traditional ...
• #### Gaussian Polynomial Filters and Generalized Shift-Invariant Frames ﻿

(December 2)
We present and study a family of filters on $L^2(\mathbb{R}^d)$ consisting of Gaussian polynomials. That is, multipliers in the frequency domain that are products of polynomials and Gaussians. These filters are constructed ...
• #### Geometric Multiscale Analysis and Applications to Neuroscience Imaging ﻿

(2017-08)
This thesis is concerned with the development of quantitative methods for the analysis of neuronal images. Automated detection and segmentation of components of neurons in fluorescent images is a major goal in quantitative ...
• #### Geometric Multiscale Representations and Applications to the Analysis to Retinal Fundus Images ﻿

(2020-05)
Systematic diseases, such as diabetes, are known to cause quantifiable changes to the geometry of the retinal microvasculature. This microvasculature is the only part of the human circulation that can be visualized ...
• #### Image Analysis Using Directional Multiscale Representations and Applications for Characterization of Neuronal Morphology ﻿

(2015-12)
Recent advances in high-resolution fluorescence microscopy have enabled the system- atic study of morphological changes in large populations of cells induced by chemical and genetic perturbations, facilitating the discovery ...
• #### Information Fusion for Multi-Source Data Classification ﻿

(December 2)
Multi-source data, either from different sensors or disparate features extracted from the same sensor, are often valuable for data analysis due to their potential for providing complementary information. Effective fusion ...
• #### Region-of-Interest Reconstruction from Truncated Cone-Beam CT ﻿

(August 201)
This thesis presents a novel algorithm in 3D computed tomography (CT) dedicated to accurate region of interest (ROI) reconstruction from truncated cone-beam projections. Here data acquisition involves cone-beam x-ray sources ...
• #### SEARCHLIGHT CT: A NEW REGULARIZED RECONSTRUCTION METHOD FOR HIGHLY COLLIMATED X-RAY TOMOGRAPHY ﻿

(2012-05)
This thesis introduces a new method for image reconstruction in collimated Computed Tomography called Searchlight CT. The method significantly reduces the overall radiation exposure when primarily the reconstruction of a ...
• #### Semi Supervised Machine Learning and Deep Learning Based Analysis for Hyperspectral Remote Sensing Images ﻿

(2019-08)
Hyperspectral Image Analysis has been an active area of research, especially in scenarios where discriminative features from classes having similar spectral characteristics have to be learned. We propose and implement novel ...
• #### Semi-supervised and Deep Learning for Hyperspectral Image Analysis ﻿

(2017-05)
Hyperspectral imaging is a technique which uses hyperspectral sensors to collect spectral information across the electromagnetic spectrum for each pixel in the image of a scene, with the purpose of identifying materials ...
• #### Semi-Supervised and Deep Learning in Optimal Subspaces for Classification of Disparate Hyperspectral Data ﻿

(2017-08)
Recent developments in remote sensing allow us to acquire enormous quantities of data via ground-based, airborne, and spaceborne platforms. Hyperspectral imagery (HSI) is a special type of remote sensing data, which not ...
• #### Spectral Angle-Based Feature Extraction and Sparse Representation-Based Classification of Hyperspectral Imagery ﻿

(December 2)
Remote sensing involves measuring and analyzing objects of interests through data collected by a remote imaging modality without physical contact with the objects. Hyperspectral sensors have become increasingly popular for ...
• #### Superpixel Based Active Learning and Online Feature Importance Estimation for Hyperspectral Image Analysis ﻿

(December 2)
The rapid development of multi-channel optical imaging sensors has led to increased uti- lization of hyperspectral data for remote sensing. For classification of hyperspectral data, an informative training set is necessary ...