1 / 6

How Facial Recognition Works with Machine Learning | IABAC

Explore how facial recognition leverages machine learning to identify and verify individuals. Learn the process of face detection, feature extraction, and pattern matching, along with applications, challenges, and the role of AI in enhancing accuracy and security.

IABAC
Télécharger la présentation

How Facial Recognition Works with Machine Learning | IABAC

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. How Facial Recognition Works with Machine Learning iabac.org

  2. Introduction to Facial Recognition Facial recognition is a technology that identifies or verifies a person using their facial features. It is widely used in security, authentication, and social media applications. Modern systems rely heavily on machine learning to improve accuracy. iabac.org

  3. Key Steps in Facial Recognition Face Detection: Locate a face in an image or video. Feature Extraction: Identify unique facial landmarks (eyes, nose, mouth, contours). Face Representation: Convert facial features into a numerical format (feature vectors). Matching & Recognition: Compare feature vectors against a database for identification or verification. iabac.org

  4. Role of Machine Learning Machine learning models, particularly deep learning and convolutional neural networks (CNNs), analyze facial patterns. The system learns from large datasets of labeled faces to recognize variations in lighting, angles, and expressions. Continuous training improves accuracy and reduces false matches. iabac.org

  5. Applications & Challenges Applications Security and surveillance Smartphone unlock and identity verification Attendance tracking and personalized experiences Challenges Privacy concerns and data security Bias in datasets leading to accuracy disparities Environmental factors affecting recognition (lighting, occlusion) iabac.org

  6. Thank you Visit: www.iabac.org iabac.org

More Related