首页|Study Findings on Machine Learning Reported by a Researcher at University of Kufa (Face Recognition approach via Deep and Machine Learning)
Study Findings on Machine Learning Reported by a Researcher at University of Kufa (Face Recognition approach via Deep and Machine Learning)
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Researchers detail new data in artificial intelligence. According to news reporting originating from the University of Kufa by NewsRx correspondents, research stated, “Face recognition is a biometric technology that involves identifying and verifying individuals based on their facial features.” Our news editors obtained a quote from the research from University of Kufa: “It finds applications in security, surveillance, and user authentication systems. The extraction of facial image features and classifier selection are more challenging to identify with conventional facial recognition technologies, and the recognition rate is lower. The paper present proposed model combined between deep wavelet scattering transform network regarding the extraction of features and machine learning for classification purposes. The proposed model consists four stage: obtaining images, performing pre-processing, extracting features, and then applying classification techniques. using both SoftMax classifier (part of deep learning model) and Support Vector Machine classifier (SVM). We used property collected dataset called MULB dataset. The experimental result shows that SVM classifier provide better results than SoftMax classifier.”
University of KufaBioengineeringBiometricsBiotechnologyCybersecurityCyborgsEmerging TechnologiesFace RecognitionMachine LearningSupport Vector MachinesTechnology
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