Machine Learning in Forensic Evidence Examination by Niha Ansari(.PDF)

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Machine Learning in Forensic Evidence Examination: A New Era by Niha Ansari
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Overview: The availability of Machine Learning algorithms, and the immense computational power required to develop robust models with high accuracy, has driven researchers to conduct extensive studies in forensic science, particularly in the identification and examination of evidence found at crime scenes. Machine Learning in Forensic Evidence Examination discusses methodologies for the application of Machine Learning (ML) to the field of forensic science. Evidence analysis is the cornerstone of forensic investigations, examined for either classification or individualization based on distinct characteristics. Artificial Intelligence (AI) offers a powerful advantage by efficiently processing large datasets with multiple features, enhancing accuracy and speed in forensic analysis to potentially mitigate human errors. Algorithms have the potential to identify patterns and features in evidence such as firearms, explosives, trace evidence, narcotics, body fluids, etc. and catalogue them in various databases.
Genre: Non-Fiction > Tech & Devices

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