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In forensic sciences, the analysis of physical evidence plays a crucial role in identifying individuals or understanding the context of certain events. Fingerprint analysis is traditionally employed for person identification, but this study aims to address a different challenge: determining the gender of an individual based on fingerprint images using artificial intelligence (AI). This work explores whether gender classification, a task typically requiring significant expertise and domain knowledge, can be performed effectively through convolutional neural networks. The central question is whether AI models can uncover subtle patterns in fingerprint images that distinguish male and female characteristics, even when such patterns are not easily discernible by humans.

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AI-Driven Biometric Intelligence: Gender Prediction via CNN-Based Fingerprint Analysis

  • 章节

  • 发表日期：

    2026年

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  • María Díaz,
  • Jayesh Soni

摘要

In forensic sciences, the analysis of physical evidence plays a crucial role in identifying individuals or understanding the context of certain events. Fingerprint analysis is traditionally employed for person identification, but this study aims to address a different challenge: determining the gender of an individual based on fingerprint images using artificial intelligence (AI). This work explores whether gender classification, a task typically requiring significant expertise and domain knowledge, can be performed effectively through convolutional neural networks. The central question is whether AI models can uncover subtle patterns in fingerprint images that distinguish male and female characteristics, even when such patterns are not easily discernible by humans.