Harnessing Deep Learning for Advanced Video Forensics in Application Software Development

Abstract

This chapter explores the integration of deep learning in video forensics, highlighting its effectiveness in large datasets and complex patterns in application software development. Deep learning algorithms are applied to enhance video analysis accuracy and efficiency by detecting, extracting, and interpreting critical information, replacing traditional methods with automated, reliable, and timely results. Advancements in convolutional neural networks, recurrent neural networks, and generative adversarial networks have been explored for image recognition, data analysis, and anomaly detection. This chapter also illustrates the practical applications of deep learning technologies in crime scene investigation, surveillance, and legal proceedings. Deep learning techniques are being integrated into video forensics, enhancing investigative capabilities and precision in digital evidence analysis.