Mathematical Foundations of Artificial Intelligence in Criminal Justice and how they are applied in Forensic Analysis
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Mathematical Foundations, Forensic Analysis, Criminal Justice, Artificial Intelligence
Abstract
In this review, we have considered the mathematical concepts that may be of most usefulness in the view of crime science. It will start by giving a high-level overview of the methodologies that are likely to be used with special attention given to complexity science methods. One will find out how mathematics is stimulated in image processing, and how image processing can improve the methods in mathematics. Mathematics is the keystone of any artificial neural network, and the initial steps to its construction can be made through the study of the principles of neural networks. Forensic analysts use mathematics to rebuild crimes, evaluate evidence, and compute timing so as to offer objective, quantitative, and scientifically valid methods. It uses trigonometry, probability, and statistics in areas of toxicology, DNA profiling, and bloodstain analysis to transform physical clues to evidence-based conclusions. This chapter addresses the issue of forgetting the prerequisites by the researchers. You will have a birds-eye view of the matter in this chapter as you find out the meaning of some of the requirements such as Image processing mathematics, forensic image processing mathematics (which comprises the basics of the neural networks) and prob ability theory. The forensic sciences extensively make use of the concepts of probability density. The concepts that were discussed during the briefing seem to belong to different areas of research but, in fact, are highly interrelated and will provide the reader with a general idea about the given topic. Section two provision of links between mathematics, image processing and forensic science and Section one is dedicated to mathematics of image processing.
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