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Found 2 papers, 1 papers with code
Improvising the Learning of Neural Networks on Hyperspherical Manifold
First, the stereographic projection is implied to transform data from Euclidean space ($\mathbb{R}^{n}$) to hyperspherical manifold ($\mathbb{S}^{n}$) to analyze the performance of angular margin losses.
COVID-19 Classification Using Staked Ensembles: A Comprehensive Analysis
Thirdly, stacked ensembles techniques are imparted to provide higher generalisation on combining the fine-tuned models, in which six ensemble neural networks are designed by combining the existing fine-tuned networks.
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