DSFormer is a novel Dual Selective Fusion Transformer Network for HSI classification. It adaptively selects and fuses features from diverse receptive fields to achieve joint spatial-spectral context ...
Abstract: In bioinformatics, the exact classification of DNA sequences is essential to increasing comprehension of genetic structures and functionalities. This research introduces an enhanced Naive ...
Abstract: Data discretization plays a critical role in enhancing the performance of the naive Bayes classifier. Traditional data discretization methods often utilize a two-stage framework, where data ...
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