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How can a single fully convolutional neural network (FCN) perform on object detection? We introduce DenseBox, a unified end-to-end FCN framework that directly predicts bounding boxes and object class confidences through all locations and scales of an image. Our contribution is two-fold. First, we show that a single FCN, if designed and optimized carefully,(More)
Face Recognition has been studied for many decades. As opposed to traditional hand-crafted features such as LBP and HOG, much more sophisticated features can be learned automatically by deep learning methods in a data-driven way. In this paper, we propose a two-stage approach that combines a multi-patch deep CNN and deep metric learning, which extracts low(More)
Viola et al. have introduced a rapid object detection framework based on a boosted cascade of simple feature classifiers. In this paper we extend their work and achieve two contributions. Firstly, we propose a novel feature definition and introduce a feature shape mask to represent it. The defined features are scale-invariant which means the features can be(More)
本文结合CSMA/CA与TDMA思想的方式,通过利用节点在网络中能感知到其他节点成功传输的特点,使节点选取在上一个虚拟TDMA周期中是第i个成功发送数据的顺序作为在当前虚拟TDMA周期中的发送顺序。由于同一时隙有且仅有一个成功传输的节点,那么所有成功传输的节点都有一个独立的时隙来发送数据,未成功的节点则随机选取剩余的时隙中某一个再次发送数据。这样成功节点间的数据发送不会相互干扰,未成功节点也不会影响到成功节点的传输。并且在一个虚拟TDMA周期中,当所有节点都能成功发送一次数据时就能一直延续下去,实现免碰撞从而获得高吞吐量。
In this paper, we propose a fast and robust face detection method. We train a cascade-structured classifier with boosted haar-like features which uses intensity information only. To speed up the process, we integrate motion energy into the cascade-structured classifier. Motion energy can represent moving the extent of the candidate regions, which is used to(More)
In the motion control of the sensorless permanent magnet synchronous motor system, the accurate detection of the rotor position at low or zero speed can improve control precision and enhance reliability. In this paper, a sliding mode observer is proposed based on the high frequency signal injection to estimate rotor position of the sensorless permanent(More)
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