Aiding Forensic Investigation Through Deep Learning and Machine Learning Frameworks (Premier Reference Source: Advances in Digital Crime, Forensics, and Cyber Terrorism)

ISBN 10: 1668445581 / ISBN 13: 9781668445587

Published by Information Science Reference, 2022

About this Item

Seller Inventory # ABLING22Oct2817100186400

Bibliographic Details

• Title: Aiding Forensic Investigation Through Deep Learning and Machine Learning Frameworks (Premier Reference Source: Advances in Digital Crime, Forensics, and Cyber Terrorism)
• Publisher: Information Science Reference
• Publication Date: 2022
• Language: English
• ISBN 10: 1668445581
• ISBN 13: 9781668445587
• Binding: Hardcover
• Condition: New

About this title

Synopsis

It is crucial that forensic science meets challenges such as identifying hidden patterns in data, validating results for accuracy, and understanding varying criminal activities in order to be authoritative so as to hold up justice and public safety. Artificial intelligence, with its potential subsets of machine learning and deep learning, has the potential to transform the domain of forensic science by handling diverse data, recognizing patterns, and analyzing, interpreting, and presenting results. Machine Learning and deep learning frameworks, with developed mathematical and computational tools, facilitate the investigators to provide reliable results. Further study on the potential uses of these technologies is required to better understand their benefits.

Aiding Forensic Investigation Through Deep Learning and Machine Learning Frameworks provides an outline of deep learning and machine learning frameworks and methods for use in forensic science to produce accurate and reliable results to aid investigation processes. The book also considers the challenges, developments, advancements, and emerging approaches of deep learning and machine learning. Covering key topics such as biometrics, augmented reality, and fraud investigation, this reference work is crucial for forensic scientists, law enforcement, computer scientists, researchers, scholars, academicians, practitioners, instructors, and students.

About the Author

Vijayalakshmi G. V. Mahesh received her BE in Electronics and Communication Engineering from Bangalore University, India in 1999, and M.Tech in Digital Communication and Networking from Visvesvaraya Technological University in 2005 and the Ph.D. degree from the Vellore Institute of Technology, Vellore, India. Currently she is working as an Associate Professor at BMS Institute of Technology and Management, Bangalore, India. She has been in academics for over 19 years and has published her research in various reputed journals and conferences. Dr. Vijayalakshmi is serving as academic editor for various journals. She has edited and published two books " Handbook of Research on Deep Learning-Based Image Analysis Under Constrained and Unconstrained Environments" and " Aiding Forensic Investigation Through Deep Learning and Machine Learning Frameworks" with IGI Global publishers. Her research interests include Machine Learning, Image Processing, Pattern Recognition and Deep learning, Affective computing.