A Patch-Based Computational Framework for the Analysis of Structurally Heterogeneous Bioelectrographic Images

Image datasets characterized by high intra-image structural heterogeneity pose significant challenges for supervised classification, particularly when local patterns contribute unevenly to image-level decisions. In such scenarios, direct image-level learning may obscure relevant local variability an...

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書誌詳細

主要な著者:	Rodrigo Guedes Pereira Pinheiro, Claudia Lage Rebello da Motta
フォーマット:	Artigo
言語:	Inglês
出版事項:	MDPI AG 2026-02-01
シリーズ:	Applied Sciences
主題:	patch-based image analysis computer vision morphological pattern classification hierarchical image data class imbalance decision threshold calibration
オンライン･アクセス:	https://www.mdpi.com/2076-3417/16/4/1907
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