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Traditional vehicle detectors always utilize singletemplate model to represent the vehicle which can not encircle vehicles with different aspect ratios. In this paper, we propose a fast and accurate approach for detecting vehicles which joints classification and aspect ratio regression. The key idea is extending the boosting decision trees method to estimate vehicle's aspect ratio during vehicle detection,...
Crowd counting on still images is very challenging due to heavy occlusions and scale variations. In this paper, we aim to develop a method that can accurately estimate the crowd count from a still image. Recently, convolutional neural networks have been shown effective in many computer vision tasks including crowd counting. To this end, we propose a fully convolutional network (FCN) architecture to...
Flow pattern is one of the most important parameters for gas-liquid two-phase flow. In this work, a new flow pattern identification method based on Convolution Neural Network (CNN) is presented. A 7-layer CNN structure is chosen, and the parameters of this network are determined by a training set. In order to verify the feasibility, experiments were carried out in horizontal pipe with the inner diameter...
In conventional echo stat network (ESN), the reservoir are randomly generated, then the spectral radius of the reservoir is scaled to lower than 1. In this method, only the necessary condition for echo state property (ESP) of ESN is satisfied while the sufficient condition is ignored, thus the ESN stability may not be ensured. In this paper, with the predefined singular values (smaller than 1), the...
In data classification mining, the decision tree method is a key algorithm. ID3 (Iterative Dichotomiser 3) algorithm which was presented by Quinlan is a famous decision tree algorithms, but ID3 has some shortcomings such as high complex computation in computing the information entropy expression, multivalue bios problem in the process of selecting an optimal attribute, large scales, etc. In order...
Considering the problems of low recognition rate and poor robustness in traditional recognition algorithms, we propose a license plate character recognition algorithm based on convolution neural network. In this paper, we adopt a coarse-to-fine strategy for designing the network architecture. Through the convolutional layers and pooling layers, features of input images will be extracted and then sent...
The multilayer perceptrons (MLPs) have been widely used in many communication applications, however, the learning process of the multilayer perceptrons often becomes very slow, which is due to the existence of the singularities in the parameter space. As the singularities significantly affect the learning dynamics of MLPs, the standard gradient descent method is not Fisher efficient. In order to overcome...
This paper evaluates the performance of four artificial intelligence algorithms for building energy consumption prediction. The backward propagation neural network (BPNN), support vector regression (SVR), adaptive network-based fuzzy inference system (ANFIS) and extreme learning machine (ELM) methods are reviewed and their performances for predicting building energy consumption are compared. A selection...
The QRS complex detection methods have been extensively studied over the past several decades, and the current common QRS detection algorithms can achieve high detection accuracy on the open-access ECG database. Although massive of researches exist on the performance of QRS detectors, the effect of the ECG signal gain is usually ignored and did not attract researchers' attentions in the past studies...
In this paper, we propose an indoor video-based feature recognition method to detect the fall behaviors of people. We firstly establish and update the video background using Gaussian mixture model, and apply background subtraction to extract the moving targets. To remove the shadow interference on these extracted moving targets, we eliminate these shadows by integrating color and gradient features...
This paper aims to develop a framework for vehicle type classification using convolutional neural network based on vehicle rear view images. Compared with the extraction of the appearance features from vehicle side view and frontal view images, there has been relatively little research on vehicle type classification by using vehicle rear view images' information. The vehicle rear view images are detected...
In order to reduce the number of accidents caused by the call when the driver was driving, this paper uses the computer vision technology to dectet the behavior of the driver. Based on the constrained local models (CLM) to detect the characteristic changes of the mouth area, combine the HSV color space and the template matching to detect the hand characteristics to judge whether the driver has the...
High quality teaching has always been the pursuit of universities, but the automatic and real time evaluation on the quality of classroom teaching has not been achieved. To solve this problem, a real-time processing of classroom video through face detection technology and a software system to provide a basis for judging the quality of teaching is proposed in this paper. The main application of machine...
In the enterprise training, a digital telephone system with special functions is needed and there are no such products on the market. In this paper, a digital telephone system for training is designed based on CAN (Controller Area Network) bus and Ethernet. The SPC (Stored Program Controlled) telephone exchange is designed with distributed multi processors which communicate by CAN. In the system,...
In this paper, the face modeling problem, a random forest model on each feature point by pixel difference feature, by regression estimation of forest model shape training samples; to estimate the shape of training samples for linear least squares fitting and real shape, a global optimization model; and then use the model to test the sample feature point location regression estimation and shape optimization,...
In this paper, we presented an improved vehicle detection algorithm based on object proposals. In the training part, by using Selective Search algorithm, we firstly segment the vehicle areas in the sample set as positive examples, other regions as negative examples. Then PHOG (Pyramid Histogram of Oriented Gradient) features of the positive samples and negative ones after separately being labeled...
In order to realize autonomous landing of the unmanned aerial vehicle (UAV) in power patrolling, a visual method vision based on Faster Regions with Convolutional Neural Network (Faster R-CNN) for UAVs is studied. In this paper, we design the landing sign of the combination of concentric circles and pentagon, and propose the Faster R-CNN recognition algorithm which can be used to identify the target...
In this paper, by learning the origin of the word distributed representation, knowing the distributed representation is one of the bridges of natural language processing mapping to mathematical calculations. Through the learning distributed representation model: neural network language model, CBOW model and Skip-gram model, the advantages and disadvantages of each model are clarified. Through the...
The purpose of this study was to investigate changes of the maximal reaching distance (MRD) and the amplitude of electromyography (EMG) in lower limbs during reaching forward (RF) test with outstretched arm in the elderly. Ten healthy elderly subjects and ten healthy young subjects participated in this study. A position sensor was used to record the position coordinates of fingertip, and the EMG signals...
Food safety is one of the hot issues in all over the world. It is related to national economy and people's livelihood. In recent years, food safety accidents occur in China frequently, so an effective food safety network public opinion early warning model is necessary and imperative. Therefore, the model of Back Propagation neural network based on Analytic Hierarchy Process (AHP-BP) is proposed. The...
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