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Backpropagation in neural networks step-by-step explained
Understand the Maths behind Backpropagation in Neural Networks. In this video, we will derive the equations for the Back ...
Abstract: Vision transformers have demonstrated remarkable performance in hyperspectral image classification tasks. However, their complex computational mechanisms and excessive parameterization ...
Abstract: Hyperspectral images (HSIs) containing tens to hundreds of bands can be used in various image classification tasks. However, due to the high data redundancy of the spectral information, the ...
This repository contains a Python package that implements the k-Nearest Neighbors (k-NN) algorithm for classifying Iris flowers into three species: setosa, versicolor, and virginica. The package uses ...
Williams, A. and Louis, L. (2026) Cumulative Link Modeling of Ordinal Outcomes in the National Health Interview Survey Data: Application to Depressive Symptom Severity. Journal of Data Analysis and ...
We provide the code (in PyTorch) and datasets for our paper "On Size-Oriented Long-Tailed Graph Classification of Graph Neural Networks" (SOLT-GNN for short), which is published in WWW-2022. (1) First ...
Objective: This study aimed to determine optimal sample sizes and the relationships between sample size and dataset-level characteristics over a variety of binary classification algorithms. Methods: A ...
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