Revolutionizing Crime Investigation
Nav Singh, Mumtaz Zabeen Khan, Balwinder Kaur, Ajitabh Mishra · 2025
As law enforcement agencies face increasingly intricate criminal cases, the incorporation of deep learning presents remarkable capabilities in data analysis, pattern recognition, and predictive modeling. This chapter commences by delineating the core principles of deep learning and its unique benefits compared to traditional forensic methods, particularly its proficiency in efficiently processing extensive datasets. The discourse further explores various applications of deep learning within forensic science, such as digital forensics, biometric identification, and crime scene reconstruction. By utilizing convolutional neural networks (CNNs) and other sophisticated algorithms, investigators can improve image analysis, automate the classification of evidence, and enhance the reliability of eyewitness identifications. Additionally, the chapter examines the challenges linked to the adoption of these technologies, including concerns regarding data privacy and algorithmic bias.