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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

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Artificial intelligence powered crime scene analysis service.

Vanita Kshirsagar¹, Nishant Pachpor², Shubhangi Suryawanshi¹

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

|July 14, 2025

Summary

This study introduces an AI-powered web application for forensic science, enhancing crime scene investigations. The tool automates fingerprint reconstruction, weapon detection, and human activity recognition, improving efficiency and accuracy in criminal justice.

Keywords:

Artificial Intelligence Crime scene analysis Deep learning Forensic science GAN Multimodal Crime seane analysis YOLO

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Area of Science:

Forensic Science
Artificial Intelligence
Computer Vision

Background:

Crime remains a significant societal issue, necessitating efficient investigative processes.
Traditional forensic methods are often manual, time-consuming, and prone to human error.
There is a need for advanced technological solutions to support law enforcement and expedite justice delivery.

Purpose of the Study:

To develop and evaluate a novel web application integrating artificial intelligence for streamlining crime scene investigations.
To automate key forensic tasks including fingerprint reconstruction, weapon detection, and human activity recognition.
To provide forensic investigators with an efficient tool for analyzing crime scene data.

Main Methods:

Development of a web application with an intuitive interface for uploading crime scene images and videos.
Implementation of an autoencoder model for fingerprint reconstruction.
Utilization of YOLO NAS for object detection (weapon recognition).
Application of VGG16 for human activity recognition.

Main Results:

The fingerprint reconstruction model achieved a validation loss of 0.0477 and step loss of 0.0487, improving the analysis of partial fingerprints.
YOLO NAS demonstrated a mean Average Precision (mAP) of 77.8% for weapon detection.
VGG16 achieved a high accuracy of 98.21% for human activity recognition.

Conclusions:

The AI-driven web application significantly enhances the efficiency and accuracy of crime scene investigations.
Automated analysis of fingerprints, weapons, and human activities aids in identifying perpetrators and understanding events.
This technology offers a promising advancement for forensic science and the administration of justice.