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AI-Driven Approaches to Reshape Forensic Practices: Automating the Tedious, Augmenting the Astute

Anu Singla (Bundelkhand University, India), Shashi Shekhar (Bundelkhand University, India), and Neha Ahirwar (Bundelkhand University, India)
Copyright: © 2024 |Pages: 312
EISBN13: 9798369373187|DOI: 10.4018/978-1-6684-9800-2.ch010
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Abstract

Forensic investigation is ushering into a new era of transformation propelled by rapid technological developments and innovations. The criminals are getting smarter, and crimes are becoming more complex; in such a time dissemination of justice requires commensurate technological enhancement. This chapter explores the vast potential of AI in revolutionizing Forensic Science and provides a succinct overview into the applicability of artificial intelligence (AI) and machine learning (ML) to facilitate classification, characterization, discrimination, differentiation, and recognition of forensic exhibits. This chapter further delves into the fundamental principles of supervised, unsupervised, semi-supervised, and reinforcement learning approaches and describes common ML methods which are frequently employed by researchers of this field.
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