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The quasi-likelihood algorithm detection of rectangle ultra-wideband quasi-radiosignal with unknown amplitude, initial phase and duration has been synthesized. The statistical characteristics of the efficiency synthesized detection algorithm — false alarm probability and probability of missing a signal, have been found.
In a MIMO wireless communications system, a space-time block code specifies how the data symbols are transmitted over different antennas at different time instants. A hybrid space-time code attempts to obtain some of the available diversity and multiplexing gains, achieving low error probability and high data rate. The LD StBc-VBLAST hybrid code layers one spatial-multiplexing antenna (to increase...
In order to improve the detection probability of range-spread targets in white Gaussian noise, a detector using waveform contrast is proposed based on multiple-pulse trains. Firstly, sliding cross correlation is utilized to eliminate the detrimental influence of range migration. Then, arithmetic mean algorithm is adopted to synthesize the final high-resolution range profiles (HRRPs). Finally, the...
In this paper, we investigate a weakly-supervised object detection framework. Most existing frameworks focus on using static images to learn object detectors. However, these detectors often fail to generalize to videos because of the existing domain shift. Therefore, we investigate learning these detectors directly from boring videos of daily activities. Instead of using bounding boxes, we explore...
Detecting pedestrians that are partially occluded remains a challenging problem due to variations and uncertainties of partial occlusion patterns. Following a commonly used framework of handling partial occlusions by part detection, we propose a multi-label learning approach to jointly learn part detectors to capture partial occlusion patterns. The part detectors share a set of decision trees via...
This paper deals with an unsupervised approach for land change detection and extraction using bitemporal and multispectral remotely sensed images. It is a statistical approach based on multivariate alteration detection (MAD) transformation combined with a new ChiMerge thresholding method. As opposed to most other multivariate change detection schemes the MAD technique is invariant to affine transformations...
This article describes a method for recognizing Ukrainian car's license plates of the most common format, which has a high percentage of correct recognition and applied in practice.
Automatically describing an image with a natural language has been an emerging challenge in both fields of computer vision and natural language processing. In this paper, we present Long Short-Term Memory with Attributes (LSTM-A) - a novel architecture that integrates attributes into the successful Convolutional Neural Networks (CNNs) plus Recurrent Neural Networks (RNNs) image captioning framework,...
Recent approaches for high accuracy detection and tracking of object categories in video consist of complex multistage solutions that become more cumbersome each year. In this paper we propose a ConvNet architecture that jointly performs detection and tracking, solving the task in a simple and effective way. Our contributions are threefold: (i) we set up a ConvNet architecture for simultaneous detection...
In this paper, as binary modulation schemes, the differential on-off keying (DOOK) system, which can achieve anti-background noise capability and high data transmission efficiency, is considered. In order to solve the synchronization slip, a visible-light framed DOOK system embedding {-1,+1}-synchronization signal pattern is proposed. Moreover, theoretical formulas of detection and false alarm probability...
In this paper the design of an optimal filter for noise reduction in the readout of a charge coupled device (CCD) with applications in particle detection is presented. The proposed approach uses measured data of the noise at the output amplifier of the CCD to obtain the coefficients of a filter that minimizes the pixel variance. The preliminary results show that this approach outperforms the standard...
To better characterize movement-related neurophysiological change, the authors propose to measure not only neural activity through the electroencephalogram (EEG) but also cerebral blood flow (CBF) using a new technology, near-infrared diffuse correlation spectroscopy (DCS). A preliminary trial is described, in which EEG, DCS, and exerted force were simultaneously recorded during a cue-triggered hand...
Adaptive radar detection and estimation schemes are often based on the independence of the training data used for building estimators and detectors. This paper relaxes this constraint and deals with the non-trivial problem of deriving detection and estimation schemes for joint spatial and temporal correlated radar measurements. In order to estimate these two joint correlation matrices, we propose...
In object tracking, a novel tracking framework which is called “Tracking-Leaning-Detection” was proposed by Zdenka Kalal. This framework decomposes the object tracking task into tracking, learning and detection. In every frame that follows, the tracker and the detector work simultaneously to obtain the location of the object independently, and the learning acts as an information exchanging center...
A new self-learning method is proposed to detect sound spectral components in cochlear nerve firing patterns. The row-wise autocorrelation images from cochlear nerve firing patterns are employed to determine frequency specific autocorrelation masks. Afterwards, these masks are cross-correlated with the cochlear nerve autocorrelation pattern of unknown sound to detect spectral component amplitudes...
Most existing weakly supervised localization (WSL) approaches learn detectors by finding positive bounding boxes based on features learned with image-level supervision. However, those features do not contain spatial location related information and usually provide poor-quality positive samples for training a detector. To overcome this issue, we propose a deep self-taught learning approach, which makes...
As wireless technologies continue to advance the radio spectrum has become more congested. Spectrum utilization can be enhanced considerably by allowing a secondary user to use a licensed band when the primary user (PU) is not present. Cognitive radio (CR) promotes the efficient use of the spectrum. Cyclostationary detection is a method for detecting primary user transmissions by taking advantage...
Tracking-by-detection has become a popular tracking paradigm in recent years. Due to the fact that detections within this framework are regarded as points in the tracking process, it brings data association ambiguities, especially in crowded scenarios. To cope with this issue, we extended the multiple hypothesis tracking approach by incorporating a novel enhancing detection model that included detection-scene...
Lenslet images that record both spatial and angular light radiance in a super high definition with distinct macropixel structures desire efficient compression methods for promoting the applications of handheld plenoptic cameras urgently. In this paper, a lenslet image compression method is proposed. First, a reversible image reshaping and adaptive interpolation is proposed to align the macropixel...
We propose a scheme of multi-channel quantum random generator based on superluminescent LED (SLED), which can use only one laser source to generate independent random bit sequences parallelly. By using dense wavelength division multiplexing (DWDM) module with 100 GHz interval, we produced 10 random bit streams in different channels, every stream's generating speed reaching 2.5 Gbps. All the random...
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