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Image Input: User uploads or captures an image. Face Detection (MTCNN): The MTCNN detects facial regions and extracts bounding boxes with five key facial landmarks (eyes, nose, mouth corners). Face ...
aArtificial Intelligence in Medicine Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA bDepartment of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer ...
Abstract: Facial recognition systems are widely used in various applications such as security, healthcare, and authentication, but face significant challenges in uncontrolled environments. Poor ...
Abstract: This paper presents a decision-aid framework for face authentication detection that integrates ResNext50 with Bidirectional Long Short-Term Memory (BiLSTM) networks to enhance media ...
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