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Fall-related injuries of elderly people have become a major public-health burden resulting in direct physical, physiological and financial costs to the surfer and indirect societal costs. Automated fall detectors play a central role in reducing these damages and in supporting safety and independency of the seniors. Typically, automated fall detection devices can send real time notifications to the...
The paper describes the tests of the prototype detector mini ELITPC conducted at IFIN-HH in Romania in 2016. The mini ELITPC detector was built for the development of the ELITPC detector — an active target time projection chamber designed to investigate reactions of interest for nuclear astrophysics, especially synthesis of oxygen. These will be investigated by time inversed photodisintegration reactions...
Here, an approach for synthesizing large-area and high-quality MoS2 flakes was developed. In addition, we made up the MoS2 photoelectric detector and studied the photocurrent response of the detector. We firstly used the ceramic pieces to control MoO3 evaporation for obtaining large-area MoS2. Our CVD reaction is hydrogen free, very simple operation, high repetition rate and cost saving. The obtained...
Different types of traffic signs has different colors and shapes located in uncontrolled traffic environments. The detection of different types of traffic signs is a difficult problem in pattern recognition and computer vision. In our study, a region of interest (ROI) extraction method is proposed to extract ROI using color contrast in local regions. We utilize the high contrast in local regions to...
Flexible printed circuit board (FPC) is a popular substrate for packaging integrated circuits (ICs). Detecting the circles rapidly on FPCs by using computer vision is very important to assess the quality of FPCs during its manufacturing. In this paper, a fast circle detection approach based on a threshold segmentation method and a validation check is proposed. In the algorithm, the image is firstly...
The transport of intensity equation (TIE) has established the relationship between the phase of an optical field and the variation of its intensity along the direction of propagation. In this paper, a new method based on TIE used for two-wavelength phase retrieval has been proposed. The TIE is solved by employing the regularized Fourier-transform-based-approach under two separate wavelengths, gaining...
This paper aims to detect narrowband signal embedded in the noise background using a single acoustic vector hydrophone. In the isotropic noise field, processing on acoustic energy flow is the maximum likelihood ratio detector. Adopting ideas of the average power spectrum, we propose a narrowband detector based on the cross spectrum between acoustic pressure and acoustic particle velocity. Firstly,...
We introduce scGAN, a novel extension of conditional Generative Adversarial Networks (GAN) tailored for the challenging problem of shadow detection in images. Previous methods for shadow detection focus on learning the local appearance of shadow regions, while using limited local context reasoning in the form of pairwise potentials in a Conditional Random Field. In contrast, the proposed adversarial...
We aim for zero-shot localization and classification of human actions in video. Where traditional approaches rely on global attribute or object classification scores for their zero-shot knowledge transfer, our main contribution is a spatial-aware object embedding. To arrive at spatial awareness, we build our embedding on top of freely available actor and object detectors. Relevance of objects is determined...
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...
The requiring of large amounts of annotated training data has become a common constraint on various deep learning systems. In this paper, we propose a weakly supervised scene text detection method (WeText) that trains robust and accurate scene text detection models by learning from unannotated or weakly annotated data. With a "light" supervised model trained on a small fully annotated dataset,...
We present a novel method for detecting 3D model instances and estimating their 6D poses from RGB data in a single shot. To this end, we extend the popular SSD paradigm to cover the full 6D pose space and train on synthetic model data only. Our approach competes or surpasses current state-of-the-art methods that leverage RGBD data on multiple challenging datasets. Furthermore, our method produces...
Indoor localization for elderly monitoring is often performed using binary PIR sensors due to their advantages. However, elderly monitoring relies on good location resolution, and this latter requires large number of PIR sensors. To increase location resolution using few sensors, a multiplex binary structure is used, and to deal with ambiguities caused by such structure (e.g. zones sharing same code)...
This paper presents a zero-bias Schottky diode detector optimized for 24 GHz six-port radar applications. Based on a typical radar system, different requirements for the diode detector are derived. Moreover, a detector layout is chosen, a full mathematical model is presented and compared with Keysight ADS simulations. An optimization process is described to design a detector circuit which meets all...
An embedded device has been developed for observing stages of lung cancer. This device is based on bio-electrical impedance analysis from which reactant component has been measured to detect the stage of lung cancer. The result shows that the value of phase angle has been found very low typically below 4.5 degree from the reactant component for the patient who are in III and IV stages of lung cancer.
Background noise (BGN) measurement is intended to determine the amount of noise which appears naturally in the observed system. This paper discusses background noise (BGN) level in high voltage laboratory measured by using partial discharge current sensors: detecting impedance and high frequency current transformer. The measurement was conducted using these sensors simultaneously in five days during...
This paper is concerned with the problem of designing successful false data injection attacks in cyber-physical systems from the attacker's angle. A discrete linear time-invariant system is considered, which is equipped with a Kalman filter and a χ2 failure detector. It is assumed that the attacker cannot obtain the accurate model of the control system. Based on the inaccurate model, the method of...
We propose a framework to extend corner feature detection in standard rectangular images with less distortion to distorted circular images captured with fisheye lenses. To solve two problems of nonuniformity of spatial resolution and spherical polar coordinates singularity, our approach makes use of a modification in the Yin-Yang grid, which is an overset grid consisting of two latitude/longitude...
The signals of magnetic encoders (MEs) are a pair sinusoidal waves: a sine wave and a cosine wave. Due to many different causes, they contain error factors such as offsets, amplitude differences, phase shifts, and random noise. This paper proposes auto-calibration and noise-reduction methods to reduce these errors and to estimate the positions of MEs. This method includes auto-calibration and adaptive-bandwidth...
Research efforts have been devoted to extraction and visualization of vortices in an unsteady (turbulent) flow. Characterizing the behaviors of the flow, vortices are identifiable as regions using a vortex detector known as the lambda2-criterion. Isosurface visualization renders vortex regions based on a chosen isovalue. However, it is highly challenging to choose one isovalue suitable for visualizing...
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