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Modern scientific experimental facilities such as x-ray light sources increasingly require on-demand access to large-scale computing for data analysis, for example to detect experimental errors or to select the next experiment. As the number of such facilities, the number of instruments at each facility, and the scale of computational demands all grow, the question arises as to how to meet these demands...
IEEE 802.11b WLAN is widely used to implement Wi-Fi based Time Difference of Arrival (TDoA) indoor localization. This paper presents a novel IEEE 802.11b baseband receiver and the corresponding localization system. Frame detector and phase recovery block are dedicated to frame reception and frequency offset compensation. Baker code re-correlator is specially designed to improve anti-noise performance...
A new CMOS readout circuit with non-uniformity calibration for diode uncooled infrared focal plane array (IRFPA) is presented in this paper. A new transconductance amplifier with offset cancellation structure is proposed, utilizing output offset voltage storage. The bias current of each pixel is adjusted by a current splitting DAC array, calibrating the mismatch of the current sources and the non-uniformity...
Visual sensors are widely used in automatic parking systems, so this paper proposes an algorithm for the visual detection of available parking slots. The proposed system consists of two stages: parking slot recognition and slot occupancy classification. The parking slot recognition stage generates parking slots using the corner features of parking slot markings. The slot occupancy classification stage...
Nowadays, more and more methods have been proposed to solve the problem of face detection based on computer implementation. Due to the variations in background, illumination, pose and facial expressions, the problem of machine face detection is complex. Recently, deep learning approaches achieve an impressive performance on face detection. In this paper, a model named Multi-Scale Fusion Convolutional...
Object Tracking is an important task in Computer Vision, which has gained increasing attention from academia to industry. In this paper, we propose a real-time tracking system based on weak segmentation. Different from general tracking by detection systems, we do not classify objects into car, cat or bike, instead we just classify the image into object area and non-object area. Many tracking systems...
HBT effect of thermal light between different modes based on multi-mode interference is directly observed in a modified Michelson interferometer with orthogonal polarizations by a two-photon absorption detector at ultrashort timescale, which serves as a new unique tool for ultrafast quantum bunching distribution.
In the framework of the project SFORA in Military Institute of Chemistry and Radiometry was created a detector for the detection of biological threats. The main achievements of this project are development of a mobile device capable of analyzing the air for the presence of biological contamination and adapt it to work on the unmanned platform. The following presentation will show the results of work...
In this paper, an enhanced scheme of Index Modulation for Orthogonal Frequency Division Multiplexing (IM-OFDM), called Repeated IM-OFDM with Diversity Reception (ReIM-OFDM) is proposed. ReIM-OFDM achieves performance improvement over the convetional IM-OFDM at the same spectral efficiency by providing additional space and frequency diversity. Similar to IM-OFDM, the proposed ReIM-OFDM also activates...
In this paper, we propose efficient Zero-Forcing (ZF) Detectors based on the a Group Detection (GD) approach in order to reduce the computational cost of the conventional linear detectors when they are adopted in Massive MIMO systems. Using the GD, we first divide a Massive MIMO system into two MIMO ones with smaller dimensions. Then, we apply the conventional ZF detector to the sub-systems to recover...
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.
Brain machine interfacing (BMI) needs continuous analyses of ongoing brain activity. For a successful interaction, related brain activities and events should be reliably detected; using various approaches including machine learning techniques. To this end, a variety of characteristic signal features as well as different types of classifiers can be used. One possible application of such an interaction...
Classification of human actions is very challenging and important in many video-based applications. Two common features, i.e., the hand-crafted and the deep-learned ones are usually adopted for video representation and have been proven to be effective in many famous datasets in the literature. However, the hand-crafted feature lacks the ability to detect the discriminative and semantic features and...
Spectrum sensing is a method which is used to find out whether the channel is idle or not in Cognitive Radio Network (CRN). Traditional methods are not much reliable due to the uncertain noise during the detection. In this paper, a weighted cooperative spectrum sensing strategy with jointing energy and spectrum-width detection under noise uncertainty is proposed to improve the detection performance...
We introduce a low-complexity layered iterative sampling algorithm for near-optimal detection in uplink massive multiple-input multiple-output (MIMO) systems based on the Gibbs sampling. In contrast to the most of Gibbs-sampling-based detectors in the previous arts, which assuming the numbers of transmitting and receiving antennas are similar, in this paper we assume the number of receiving antennas...
The development of systems used to increase the energy efficiency of premises has a broad ecological and commercial importance. The most significant savings are achieved by managing lighting. There are different types of systems used for lighting control: time switches, photocells, etc. The prototype of the lighting management system that has the possibility to use several algorithms for lighting...
Compressed sensing can represent the sparse signal with a small number of measurements compared to Nyquist-rate samples. Considering the high-complexity of reconstruction algorithms in CS, recently compressive detection is proposed, which performs detection directly in compressive domain without reconstruction. Different from existing work that generally considers the measurements corrupted by dense...
Road markings are important information of transport systems for drivers or intelligent vehicle. Efficient road markings feature extraction is pre-requisite to road markings detection, recognition and visual localization. However, most of previous lane markings feature extractors are operating on conventional images, the feature extraction methods for omnidirectional images are rarely considered in...
In most convolutional neural networks (CNNs), the output is a single classification result by combining all the neuron activations in the last layer. As we know, local connectivity is an important characteristic of CNNs. Each neuron in the network corresponds to a local region in the original image. Hence, it is possible to simultaneously obtain local visibility of a target object by analyzing neuron...
This paper introduces an intelligent integrated nondestructive testing system based on active the infrared thermal wave detection. The excitation heat source of the thermal wave includes ultrasonic excitation and electromagnetic excitation and exploiting the powerful resources of computer system and LabVIEW software to develop the virtual instrument. The integrated nondestructive testing system based...
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