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Gully erosion is identified as an important sediment source in a range of environments and plays a conclusive role in redistribution of eroded soils on a slope. Hence, addressing spatial occurrence pattern of this phenomenon is very important. Different ensemble models and their single counterparts, mostly data mining methods, have been used for gully erosion susceptibility mapping; however, their...
Representation of data is very important in case of machine learning. Better the representation, the classifiers will give better results. Contractive autoencoders are used to learn the representation of data which are robust to small changes in the input. This paper uses contractive autoencoder and SVM classifier for handwritten Devanagari numerals recognition. The accuracy obtained using CAE+SVM...
Vehicle classification plays an important part in Intelligent Transport System. Recently, deep learning has showed outstanding performance in image classification. However, numerous parameters of the deep network need to be optimized which is time-consuming. PCANet is a light-weight deep learning network that is easy to train. In this paper, a new robust vehicle classification method is proposed,...
Offline signature identification and verification systems encounter several challenges such as the diversity of signatories and the limited number of references. To address these problems we propose a new writer-independent system for signature identification and verification. Besides, a new feature generation scheme is proposed by using the Histogram Of Templates (HOT). The identification and verification...
In this paper, we propose a methodology for the fusion of different modes of speaker verification (SV) operation (fixed-passphrase, text-dependent and text-independent mode), using regression fusion models. The experimental results with and without spoofing attack conditions and using different single mode speaker verification engines, GMM-UBM, HMM-UBM and i-vector, indicated improvement in all the...
This paper presents an approach to ensure first order closed loop systems stability and robustness. Actually, those systems are characterized by uncertain bounded parameters and a complex changeable structure. Delay time is also an important drawback facing most of the systems stability. Thus, the idea of this paper is to conceive a reliable and intelligent controller switched according to the SVM...
The deep learning based trackers can always achieve high tracking precision and strong adaptability in different scenarios. However, due to the fact that the number of the parameter is large and the fine-tuning is challenging, the time complexity is high. In order to improve the efficiency, we proposed a tracker based on fast deep learning through constructing a new network with less redundancy. Based...
The AC drives direct torque control (DTC) is used to obtain high performance decoupled torque and flux control. The SVM based direct torque control is a common solution which used to solve the conventional DTC's problems such as the high torque ripples and variable switching frequency. However, this control technique bases on stator flux orientation and PI controllers. This paper aims to improve the...
Copy-move Image Forgery Detection is an important topic in forensic laboratories. In this research, a hybrid method is proposed to detect the copy-move forgery in an image, by comparing extracted keypoints. Proposed scheme consists of two steps, in first step keypoints are extracted by using SIFT and then extract blocks by using kernel PCA. In second step, Extracted keypoints by using support vector...
In order to solve the detection problem of bad real-time performance and robustness in complex scene, a new method for soft cascade classifier based on SVM was built. The image features can be extracted by the algorithm of using ORBP feature descriptor. Then, based on efficiently combining manifold features and cascaded threshold, a multistage classifier frame is introduced in detail. To ensure the...
Speaker identification is a biometric technique of determining an unknown speaker's identity among a number of speakers using distinguish latent information of uttered speech. Crime investigation, security control, telephone banking and trading, and information reservation are some applications of this technique. Frequency Domain Linear Prediction (FDLP) is a time-frequency-based feature has been...
A new method for feature selection based on improved maximal relevance and minimal redundancy (mRMR) is proposed in this paper. In order to describe the influence of the added features on correlation between candidate features subset and decision, the standard mRMR was improved by introducing the calculation of parameter Sig ≥ (a, B, D). The value of Sig ≥ (a, B, D) is used to determine whether a...
Protein secondary structure prediction is an important problem in bioinformatics. For this task, a method based on the SVM-PSSM Classifier combined by sequence feature (SF) is proposed in this paper. Protein sequence data is represented by a hybrid formation which combines the Position-Specific Scoring Matrix (PSSM) with the Hydrophobicity Sequence Feature (HSF), and the Structural Sequence Feature(SSF)...
The detection of abrupt shot boundary is a fundamental task of video analytics and content-based video retrieval. The traditional methods tend to take much time in frame processing. In this paper, a GPU-accelerated abrupt shot boundary detection algorithm is proposed. This algorithm takes into account of both global feature and local feature of the video frames, in which the block HSV histograms and...
Supervised classification techniques use labeled samples in order to train the classifier. In a hyperspectral image, usually the number of such samples is limited, and as the number of bands available increases, this limitation becomes more severe. Such consequences suggest the need for reducing the dimensionality via a preprocessing method. This reduction should enable the estimation of feature extraction...
In this study, a new algorithm for Content Based Image Retrieval (CBIR) using bi-cubic interpolation (BCI)with color coding (CC) and different level of discrete wavelet transform (DWT). In this paper the techniques of CBIR are discussed, analyzed and compared. BCI is used to scale the query image and database images. CC is used for color feature extraction. Apply DWT on each level plane of an image...
Face recognition provides a challenging issue in the domain of analyzing images. In this paper a novel approach for face recognition using hybrid SIFT-SVM is proposed. The current database is divided into two parts; training and testing database. The SIFT feature will be created for each training images and the keypoints are computed; then the SVM is applied for the matching process for test images...
This paper presents an approach to audio parameterization using properties of the peaks detected in the amplitude envelope. The proposed solution based on observation that abrupt changes in the envelope of signal are connected with type of audio signal. For this purpose we used the density properties of peaks to calculate the feature vectors. The extraction process exploits an amplitude envelope estimation...
Imbalanced data is an inevitable problem in many real world problems, including bleeding detection from endoscopic videos with a fewer clinically significant examples outnumbered by normal examples. In this paper, we have presented a comprehensive analysis of six different classifier performance for different class distribution of training dataset. We have addressed two questions: 1. Is there any...
Credit risk evaluation under the background of big data has been the major focus of financial and banking industry due to recent financial crises. Recent studies have revealed that emerging modern optimization techniques are advantageous to statistical models for credit risk evaluation, such as LS-SVM. In this paper, a least squares support vector machine with mixture kernel (LS-SVM-MK) is proposed...
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