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For remote sensing image understanding, target detection is one of the most important tasks. In this paper, we propose one object detection method based on region proposal detection via active contour model and detection based on one-class classification method. The large scale remote sensing image is split into several connected components. And then, the proposed algorithm detects the object from...
Brain tumor segmentation from magnetic resonance images is a critical step for early tumor diagnosis and treatment. However, accurate and general segmentation of brain tumor is still a challenging task due to complicated characteristics of brain tumor in magnetic resonance images. To solve this problem, we proposed a novel method for brain tumor segmentation based on features of separated local square...
Diabetes is one of the most prevalent diseases worldwide, and hundreds of millions of patients are suffering from diabetes and its serious complications. Early detection and early treatment are urgent needed for clinical diagnosis of diabetics. In this work, we establish a gene coexpression network framework to identify biomarkers of transcripts with highly different gene coexpression patterns in...
Hand gesture recognition is highly valued for its potential applications in contactless human-computer interaction (HCI). Aiming at the problem that the gesture recognition system based on ordinary camera is susceptible to different lighting conditions and complex background environment, an improved algorithm based on depth image for fingertip detection and gesture recognition is proposed. Firstly,...
Efficient condition monitoring and fault diagnosis is an essential task to ensure the generation performance and reliability of photovoltaic (PV) systems. This paper proposes an online algorithm to diagnose faults of PV module based on multi-class support vector machine (M-SVM). The simulation models of the photovoltaic module are implemented and the output power generation characteristics of PV modules...
According to the noise and overlapping characteristics of agricultural irrigation water quality monitoring data for the comprehensive evaluation may bring about the boundary fuzzy problem. This paper proposes an improved Genetic Algorithm (GA) to avoid premature convergence, the global optimal solution of the function of the Projection Pursuit (PP) function is used as the comprehensive evaluation...
There are many species of tomato diseases and pests, and the pathology of which is complex. It is difficult and error-prone to simply rely on manual identification. For the ten most common tomato diseases and pests in China, This paper explores the detection algorithms on leaf images and constructs the convolution neural network model to detect tomato pests and diseases based on VGG16[8] and transfer...
For the sake of improving the precision of speech emotion recognition, this paper proposed a novel speech emotion recognition approach based on Gaussian Kernel Nonlinear Proximal Support Vector Machine (PSVM) to recognize four basic human emotions (angry, joy, sadness, surprise). Firstly, preprocess speech signal containing sampling, quantification, pre-emphasizing, framing, adding window and endpoint...
This paper presents a support vector machine (SVM) based model predictive control (MPC) strategy to manage the engine speed to the set-point of idle speed. The predictive model is trained by SVM due to its accuracy of learning nonlinear process, simple training program and no over-fitting nature. To reduce the computational burden of controller and retain the dynamic information of system, the instantaneous...
The present status of heart sound recognition is introduced in the paper. In order to improve the performance of heart sound recognition, a new model based on SVM is proposed. Firstly, the wavelet transform is used to reduce the noise of the heart sound, and then MFCC feature is extracted from heart sound. On this basis, the Support Vector Machine is used to build the classification model. In the...
At present, shallow characteristics are usually utilized to represent the distributed features of text for Chinese spam classification, causing the problem of inexact text vector representation and low classification performance. A novel Chinese spam classification method based on weighted distributed feature is proposed by combining the features of TF-IDF weighted algorithm with the distributed text-based...
VIENNA rectifier with simple structure, which is widely used in charging systems for electric vehicle, realizes the operation of unit power factor and low harmonic. However, grid voltage unbalance will aggravate the dc-link voltage ripple and input current THD. A novel control scheme is presented to solve the impacts of three unbalanced grid voltage for VIENNA rectifier in this paper. The enhanced...
For face recognition systems, impostors can obtain legal identity authentication by presenting the printed images, the downloaded images or candid videos to the sensor. In this paper, an enhanced face local binary feature (ELBP) of a face map is extracted as a classification feature to identify whether the face map is a real face or a fake face. Compared with the dynamic or static methods proposed...
Recursive projection twin support vector machine (PTSVM) and Locality preserving projection twin support vector machine (LPPTSVM) are two extensions of traditional support vector machine (SVM). However, they may lead to a weak classifier in the application where some data points may not be fully assigned to one class. In this paper, we introduce the basic idea of fuzzy membership into LPPTSVM and...
With the rapid increase in total capacity of wind turbine, condition monitoring is more essential which can efficiently guide operation and maintenance plans. The failure rate is high occurred in gearbox, while gearbox oil temperature can reflect the operating state of the transmission structure within gearbox. In this paper, fit a Support Vector Machines (SVM) regression to model gearbox oil temperature...
Unilateral medial temporal lobe epilepsy (mTLE) have similar symptom in clinic. Previous studies indicate that it's difficult to find significant differences when comparing the structure of left and right mTLE directly. As is known to all, hippocampus sclerosis often causes mTLE. Therefore, it may be essential to detect the internal structure of hippocampus (HC) to confirm the lateralization of mTLE...
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...
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 this paper, the operating conditions of vehicle internal combustion engine (ICE) waste heat utilization system are monitored by improved support vector machines (SVMs). Organic Rankine Cycle (ORC) is used to recover the ICE waste heat. Several optimal approaches are employed when training SVMs. The improved SVMs are then employed to monitor the operating conditions of the ICE waste heat recovery...
It is difficult to establish accurate mathematical models to describe the range extender electric vehicles due to the non-stationary, non-linear and interconnection of the monitoring signal sources resulted from the massive moving parts and complex architecture in range-extender. And the support vector machine (SVM) and other algorithms would lead to the destruction of the natural structure and the...
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