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Convolution-based detection models (CDM) have achieved tremendous success in computer vision in last few years, such as deformable part-based models (DPM) and convolutional neural networks (CNN). The simplicity of these models allows for very large scale training to achieve higher robustness and recognition performance. However, the main bottleneck of those powerful state-of-the-art models is the...
This paper proposes a detection approach for localizing the object of specific category in images. Based on the ensemble of exemplars, a per-exemplar classifier for each exemplar is learnt, which is simple but powerful to perform well in detecting visually similar objects. Meanwhile, considering the fact that the number of negatives is always considerably larger than that of positives, the method...
Spectrum Sensing is a cornerstone in cognitive radio which can detect the spectrum holes in order to raise spectrum utilization ratio. Traditional spectrum sensing detectors depend on some prior information or are restricted by low signal-to-noise ratio and computation complexity in practical application. A GoDec based spectrum sensing detector is proposed by combining covariance based method with...
A novel subspace method for estimating the parameters of wideband polynomial-phase signals (PPSs) in sensor arrays that exploits the characteristics of the high-order instantaneous moment (HIM) to form a model of signals received by an array is presented. The super-resolution and robustness of subspace theory is employed to estimate the direction of arrival (DOA) and coefficients of the Kth-order...
In this paper, we present an efficient algorithm for sparse signal recovery with high exact recovery rate. The main idea of the algorithm is to combine two existing methods: linearized Bregman algorithm and reweighting technique. Compared with other available methods, such as reweighted Basis Pursuit (BP) and linearized Bregman, the proposed algorithm has a much lower computational complexity with...
Order tracking technique is an effective frequency analysis method, which uses multiples of the running speed as the frequency base (orders) and commonly used in rotating machinery vibration signal analysis. It is a dedicated non-stationary vibration processing technique to detect speed-related vibrations. Angular sampling theory based computed order tracking (COT) method is the most widely used method...
Target tracking is one of the most important applications for wireless sensor networks (WSNs). It is usually assumed that the knowledge of the sensor nodes' position is known precisely. However, practically nodes are randomly deployed without prior knowledge about their own positions. In this situation, simultaneous localization and tracking (SLAT) is necessary and is receiving more and more research...
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