Designing Deep Learning Architecture for Latent Fingerprint Matching
نویسنده
چکیده
Image recognition using partial information is one of the significant problems in current computer vision research. Computer vision has an important role in medical, robotics, economics, and crime-related subjects. Complete fingerprint or face is usually not available at a crime scene or camera image. The full image or partial image of crime is common in most of the crime data. The crime branch identifies the related match of criminal’s data with the help of collected image or partial image data. In this research, we introduce the fingerprint background, classification, and deep learning artificial neural network model to identify the closest match image (fingerprint) for a given partial image (latent fingerprint) data..
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