CNNs for Face Detection and Recognition

CNNs for Face Detection and RecognitionYicheng AnDepartment of Electrical EngineeringStanford WuDepartment of Electrical EngineeringStanford YueDepartment of Electrical EngineeringStanford face Detection method is becoming a more andmore important technique in our social lives. From face de-tection technology implemented in our cheap cameras to in-telligent agencies sophisticated global skynet surveillancesystem, such techniques have been widely used in a largenumber of areas and the market is still growing with a highspeed. Face Detection has been an active research area withmany successful traditional and deep learning methods. Inour project we are introducing new convolutional neuralnetwork method to tackle the face Detection to maintain ahigh accuracy while running in real Problem StatementIn our imaginary scenario, our technique could be usedby companies and facilities with security levels: customerscould put all personnel s info into the dataset, and then putthe camera at the desired position like the office front people coming in are not in the dataset, there would be analarm; otherwise, everything should be , our method ha

One of the most significant breakthrough on object detec-tion with Region Proposals is the R-CNN developed by Gir-shick et al. [9]. First R-CNN generates approximately 2000 Regions of Interest (RoI) using the Region Proposal method on the input image, then it warps each RoI into standard in-put size for the neural network and forward them into the

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  Into, Faces, Recognition, Detection, Detec, Detec tion, For face detection and recognition

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