Bongsoon Kang

1. Introduction Deep neural networks (DNNs) have become fundamental in pattern recognition applications due to their ability to model complex data distributions and achieve state-of-the-art performance in tasks such as image classification, speech recognition, and natural language processing [1,2,3]. By leveraging hierarchical feature extraction and deep architectures, DNNs effectively capture intricate patterns and relationships within data.

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