Deep Unfolding Network for Image Super-Resolution (CVPR, 2020) (PyTorch)
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Updated
Jul 31, 2023 - Python
Deep Unfolding Network for Image Super-Resolution (CVPR, 2020) (PyTorch)
A novel architectural design for stitching video streams in real-time on an FPGA.
A 2D Gaussian Splatting paper for no obvious reasons. Enjoy!
Fast Incremental Support Vector Data Description implemented in Python
Evaluation of few methods to apply Gaussian Blur on an Image.
An Efficient Gaussian Kernel Based Fuzzy-Rough Set Approach for Feature Selection
classify mnist datasets using ridge regression, optimize the algorithem with SGD, stochastic dual coordinate ascent, and mini-batching
We use support vector machines (SVMs) with various example 2D datasets. Experimenting with these datasets will help us gain an intuition of how SVMs work and how to use a Gaussian kernel with SVMs. In the next half of the exercise, we use support vector machines to build a spam classifier.
Implementation of Kernel-Density-Estimation (KDE) with Matlab
Signal and Systems course project - Fall 2021 - voice activity detection using gaussian kernel and adaptive threshold
Statistical pattern recognition course projects from shiraz university.
Implementation of the algorithm from "Fast training of Support Vector Machines with Gaussian kernel" (Fischetti, 2016)
Computer Vision projects using python
A nonlinear classifier for categorizing shoes using machine learning
SVM with Gaussian kernel implementation for spam classification problem using numpy
Classification on the Web Spam Dataset using Percepton and Kernel Perceptron with Polynomial, Gaussian, Exponential and Laplacian Kernels.
This repository contains Materials for Non-Parametric Inference
It is based on support vector machines ,first we used linear kernel for lesser featured dataset, Gaussian kernel for more complex dataset.
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