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Non-equilibrium in the Cell01:16

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An important concept in studying metabolism and energy is that of chemical equilibrium. Most chemical reactions are reversible. They can proceed in both directions, releasing energy into their environment in one direction, and absorbing it from the environment in the other direction. The same is true for the chemical reactions involved in cell metabolism, such as the breaking down and building up of proteins into and from individual amino acids, respectively. Reactants within a closed system...
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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
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人工智能驱动的犯罪现场分析服务.

Vanita Kshirsagar1, Nishant Pachpor2, Shubhangi Suryawanshi1

  • 1Dr. D. Y. Patil Institute of Technology, Pimpri, Pune.

MethodsX
|July 14, 2025
PubMed
概括

这项研究介绍了用于法医科学的AI驱动的Web应用程序,增强犯罪现场调查. 该工具自动化了指纹重建,武器检测和人类活动识别,提高了刑事司法效率和准确性.

关键词:
人工智能的人工智能犯罪现场分析.深度学习是一种深度学习.法医科学 法医科学没有了,没有了,没有了.多式联络犯罪分析Seane分析这是一个YOLO YOLO.

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科学领域:

  • 法医科学 法医科学 法医科学
  • 人工智能的人工智能
  • 计算机视觉 计算机视觉

背景情况:

  • 犯罪仍然是一个重要的社会问题,需要有效的调查过程.
  • 传统的法医方法往往是手动的,耗时的,容易出现人为错误.
  • 需要先进的技术解决方案来支持执法和加快司法执行.

研究的目的:

  • 开发和评估一个新的网络应用程序,集成人工智能,以简化犯罪现场调查.
  • 自动化关键的法医任务,包括指纹重建,武器检测和人类活动识别.
  • 为法医调查人员提供一个有效的工具来分析犯罪现场数据.

主要方法:

  • 开发一个具有直观界面的Web应用程序,用于上传犯罪现场图像和视频.
  • 实现用于指纹重建的自动编码模型.
  • 使用YOLO NAS进行对象检测 (武器识别).
  • 应用VGG16对人类活动的认可.

主要成果:

  • 指纹重建模型实现了0.0477的验证损失和0.0487的步骤损失,改善了部分指纹的分析.
  • 在武器检测方面,YOLO NAS的平均平均精度 (mAP) 为77.8%.
  • VGG16在人类活动识别方面实现了98.21%的高精度.

结论:

  • 由人工智能驱动的Web应用程序显著提高了犯罪现场调查的效率和准确性.
  • 对指纹,武器和人类活动的自动分析有助于识别罪犯和理解事件.
  • 这项技术为法医科学和司法行政提供了有前途的进步.