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.
Results
Showing 1 to 20 of 64 for “"CONVOLUTIONS"”.
-
On Laplace transforms, generalized gamma convolutions, and their applications in risk aggregation
… and an introduction on Generalized Gamma Convolutions (GGCs). The heart of this dissertation is the final three chapters comprised of three contributions to the literature. In Chapter 3, we study the analytical properties of the Laplace transform of the log-normal distribution. Two …
-
An Extension to Orlicz Spaces of Theorems of M. M. Day on 'Convolutions, Means, and Spectra.'
Made available in DSpace on 2014-12-09T22:17:40Z (GMT). No. of bitstreams: 1 6801875.pdf: 1130721 bytes, checksum: bf6ca8d961d6d8c406416a6be53ba736 (MD5) Previous issue date: 1967
-
Analysis of a time delay controller based on convolutions, with application to a cruise control system
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1993.
-
Spectral-Iterative Analysis of Electromagnetic Radiation and Scattering Problems (radar-Cross-Section, Integral Equation)
… is tested in the same way, the continuous convolutions reduce to discrete convolutions. These operations can then be readily computed by the Fast-Fourier Transform algorithm resulting in a significant reduction in computer time. This spectral domain method of calculating convolutions is …
-
Fast and Scalable Architectures and Algorithms for the Computation of the Forward and Inverse Discrete Periodic Radon Transform with Applications to 2D Convolutions and Cross-Correlations
… applications in the computation of fast convolutions and cross-correlations for large and non-separable kernels. For this purpose, I introduce fast algorithms and scalable architectures to compute 2-D Linear convolutions/cross-correlations using the convolution property of the DPRT and …
-
Learning from videos with deep convolutional LSTM networks
… the individual frames or directly utilizing 3D convolutions within high-performing 2D CNN architectures. The focus typically remains on how to incorporate the temporal processing within an already stable spatial architecture. This research explores the use of convolution LSTMs to simultaneously …
-
Prospects for Quantum Equivariant Neural Networks
… harmonic analysis and geometric deep learning. Convolutions and cross-correlations are examples of functions which are equivariant to the actions of a group. We present efficient quantum algorithms for performing linear finite-group convolutions and cross-correlations on data stored as quantum …
-
Investigation of topics in radar signal processing
… domain image is produced through a series of convolutions and DFTs, all performed using FFTs. We show that the algorithm implements a form of trapezoidal-to-Cartesian interpolation followed by an FFT.
-
On the Fourier decay and the dimension of self-similar measures
… to be studied were the so-called Bernoulli convolutions, associated to the IFS $\lambda x, \lambda x+1$ for $\lambda \in (0.5,1)$ with equal weights, considered by Erd\H os around 1940. %For those, %\[ %\mu=\mathrm{law}\left(\sum_{j=0}^\infty \xi_j \lambda^j \right), %\] %where $\xi_j$ are …
-
ΜΕΛΕΤΗ ΤΗΣ ΥΠΟΛΟΓΙΣΤΙΚΗΣ ΠΟΛΥΠΛΟΚΟΤΗΤΑΣ ΑΛΓΟΡΙΘΜΩΝ ΤΗΣ ΨΗΦΙΑΚΗΣ ΕΠΕΞΕΡΓΑΣΙΑΣ ΠΟΛΥΔΙΑΣΤΑΤΩΝ ΣΗΜΑΤΩΝ
… DFT CALCULATION IS DEVELOPED. NEW ALGORITHMS FOR CONVOLUTIONS OVER GALOIS FIELDS ARE PRESENTED. FINALLY THE ERROR ANALYSIS IN FLOATING POINT ARITHMETIC OF THE RECTANGULAR TRANSFORM AND THE MULTIDIMENSIONAL DFTS IS PRESENTED.
-
Molecular graph Self attention and graph convolution for drug discovery
… molecules as undirected graphs and use graph convolutions and self-attention to predict molecular properties. With a series of ablation studies, we demonstrate the added value of several key components in our network. We analyze two standard datasets: BBBP, which includes classication data on …
-
Fast Waveform Pattern Matching With Significant-Point Frames
… of linear differential operators across multiple convolutions. These structures can be viewed as compressed, hierarchical representations of the signal, and have served as bases of successful systems for pattern matching The interval tree proves unsuitable, however, for representing signals of …
-
A graph-based framework for information extraction
… between connected nodes through graph convolutions, generating a richer representation that can be exploited to improve word-level predictions. Evaluation on three different tasks -- namely textual, social media and visual information extraction -- shows that GraphlE consistently …
-
Modeling Structured Data with Invertible Generative Models
… Other similar operations, such as 1x1 convolutions, emerging convolutions, or periodic convolutions allow at most two of these three advantages. In our experiments on multiple image datasets, we find that Woodbury transformations allow learning of higher-likelihood models than other …
-
NEURAL ARCHITECTURE DESIGN AND APPLICATIONS
… which decomposes large-kernel depthwise convolutions into smaller components, inspired by Inceptions. InceptionNeXt improves throughput and maintains performance, offering a more efficient baseline for future architecture design.
-
Size is everything : universal features of quasar microlensing with extended sources
… By looking at magnification histograms of the convolutions and using chi-squared tests to determine the number of observations that would be necessary to distinguish histograms associated with different disk models, we find that, for circular disk models, the microlensing fluctuations are …
-
DERMAI – A DEEP LEARNING-BASED WEB PLATFORM FOR DERMATOLOGIC DIAGNOSIS
… The diagnostic model, enhanced with large kernel convolutions and a Convolutional Block Attention Module for capsule networks, achieved 99.25% accuracy on the HAM10000 dataset. DermAI enables patients to receive preliminary skin disease diagnoses via internet, potentially improving primary care …
-
Amodal video instance segmentation
… temporal information. Specifically, we employ 3D convolutions and a flow alignment module which permits to aggregate the objects’ features across frames. Second, we develop a cascaded box-head with soft-non-maximum-suppression to address the challenge that amodal segmentations overlap …
-
Finding similar questions in large-scale community QA forums
… of recurrent and convolutional models (gated convolutions) to effectively map questions to their semantic representations. The models are pre-trained within an encoder-decoder framework (from body to title) on the basis of the entire raw corpus, and fine-tuned discriminatively from limited …
Page 1 of 4