Deep Neural Network based Image Recognition
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Image recognition is a challenging problem that has recently received much attention in computer vision and machine learning. This book presents a comprehensive overview of the problem of image recognition based on deep neural network. we present an approach to recognize digits using four models i.e. Logistic Regression Model (LRM), Support Vector Machine (SVM), Back Propagation Neural Network (BPNN) & Convolutional Neural Network (CNN). Face recognition is a biometric system used to identify or verify a person from a digital image mostly used in security and surveillance purpose. Thus, we are...
Image recognition is a challenging problem that has recently received much attention in computer vision and machine learning. This book presents a comprehensive overview of the problem of image recognition based on deep neural network. we present an approach to recognize digits using four models i.e. Logistic Regression Model (LRM), Support Vector Machine (SVM), Back Propagation Neural Network (BPNN) & Convolutional Neural Network (CNN). Face recognition is a biometric system used to identify or verify a person from a digital image mostly used in security and surveillance purpose. Thus, we are inspired to inspect the effectiveness of deep neural network on face recognition. we present a deep neural network architecture referred as HOG-CNN for face recognition. The goal is to face recognize faces in real time i.e. using webcam, from a photograph or from a set of faces tracked in a video. This book also presents an approach to recognize objects in real time i.e. using webcam, from a photograph or from a set of objects tracked in a video.
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