Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 10 of 10 for “"Sparse Reconstruction"”.
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Bayesian Methods and Machine Learning in Astrophysics
… nested sampling (Chapters 3 to 5), and Bayesian sparse reconstruction of signals from noisy data (Chapters 6 and 7). Nested sampling is a popular method for Bayesian computation which is widely used in astrophysics. Following the introduction and background material in Chapters 1 and 2, Chapter 3 …
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Computation tools for the Fourier transform infrared (FT-IR) spectroscopic imaging
… tools such as dictionary training for sparse representation, and compressive sensing. Here, we use a singular value decomposition denoising algorithm to recover the noiseless absorbance data. Then, novel variational Bayesian deconvolution algorithms using a theoretical formula of the …
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Tensor photography : exploring space of 4D modulations inside traditional camera designs
… camera architecture that allows capture and reconstruction of higher resolution light fields in a single shot. The proposed architecture comprises three key components: light field atoms as sparse representation of natural light fields, an optical design to allow capture of optimized 2D light …
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Data-efficient Neural Appearance Manipulations
… function (BRDF) representation that enables sparse reconstruction, compression, and editing. By leveraging the known or learned priors that include problem-specific information, the proposed methods address the challenge of producing high-quality and visually appealing results in data-scarce …
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Computational visual reality
… tensor factorization and dictionary-based sparse reconstruction, respectively, in conjunction with the co-design of algorithms, optics, and electronics to allow compressive, simultaneous, light field display and capture.
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Validation of a Commercial Ultrasonic Real-Time Location System for Providing Position Constraints in Low-Cost Indoor Photogrammetric Reconstruction
Indoor 3D reconstruction for building documentation faces a fundamental challenge: creating accurate, properly scaled digital models without relying on extensive ground control point (GCP) networks or specialized surveying expertise. This research investigates whether commercial ultrasonic …
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Recovery of sparse signals and parameter perturbations from parameterized signal models
… signal has few nonzero elements. If a signal is sparse in a parameterized measurement model, the model parameters must be known to recover the signal. An example of this problem is the recovery of a signal that is a sum of a small number of sinusoids. Reconstruction of this signal requires …
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Development of GPR data analysis algorithms for predicting thin asphalt concrete overlay thickness and density
… techniques are proposed, including migration and sparse reconstruction. Both algorithms were validated on GPR signals reflected from buried pipes using finite difference time domain (FDTD) simulation. Second, as a special case of the 2-D GPR imaging and linear inversion reconstruction, regularized …
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Bayesian approaches to time-frequency inverse problems
… representations and its application to audio reconstruction problems. To address the inherent ambiguity of overcomplete dictionaries, the assumed generative mechanism of the audio waveform is enriched with prior structures that not only serve as a regularisation device but also reflect …
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Image Compression and Channel Error Correction using Neurally-Inspired Network Models
… I compared bottleneck autoencoders with two sparse coding approaches. Either 50\% of the pixels are randomly removed or every other pixel is removed, each achieving a 2:1 compression ratio. In the subsequent decompression step, a sparse inference algorithm is used to in-paint the missing the …