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Recently, pedestrian attributes like gender, age and clothing etc., have been used as soft biometric traits for recognizing people. Unlike existing methods that assume the independence of attributes during their prediction, we propose a multi-label convolutional neural network (MLCNN) to predict multiple attributes together in a unified framework. Firstly, a pedestrian image is roughly divided into...
Various hand-crafted features and metric learning methods prevail in the field of person re-identification. Compared to these methods, this paper proposes a more general way that can learn a similarity metric from image pixels directly. By using a "siamese" deep neural network, the proposed method can jointly learn the color feature, texture feature and metric in a unified framework. The...
A scheme for multi-input/multi-output (MIMO) black-box system based on support vector machine (SVM) is developed. By analyzing characters of MIMO system, system inputs are decoupled each other as combination of objective function and system output. After designing transform law of objective function, system inputs are acquired directly as outputs of trained SVMs, therefore recognition and controller...
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