Criminal Identification Using Deep Learning

Crime detection and identification of criminals is an important task for law enforcement agencies.Traditional identification methods such as manual verification and fingerprint analysis are often time-consuming and require significant human effort.With the advancement of Artificial Intelligence and Deep Learning, automated facial recognition systems can improve the efficiency and accuracy of criminal identification.The proposed Criminal Identification System uses deep learning techniques to detect and recognize faces from images and match them with stored criminal records.The system captures facial images through uploaded image and processes them using convolutional neural networks (CNN) to extract unique facial features.These features are compared with the database to identify potential criminals.The system provides the identification result along with confidence scores to ensure reliability.This approach significantly reduces manual effort and improves the speed of investigation.The system can assist police departments and security agencies in identifying suspects quickly and effectively, thereby improving public safety and surveillance efficiency.