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Karyotyping, manual chromosome classification is a difficult and time consuming process. Many automated classifiers have been developed to overcome this problem. These classifiers either have high classification accuracy or high training speed. This paper proposes a classifier that performs well in both areas based on wavelet neural network (WNN), combining the wavelet into neural network for classification...
Distributed Hierarchical Graph Neuron (DHGN) is a single-cycle learning distributed pattern recognition algorithm, which reduces the computational complexity of existing pattern recognition algorithms by distributing the recognition process into smaller clusters. This paper investigates an effect of dividing and distributing simple pattern recognition processes within a computational network. Our...
Compared to the protein 3-class secondary structure (SS) prediction, the 8-class prediction gains less attention and is also much more challenging, especially for proteins with few sequence homologs. This paper presents a new probabilistic method for 8-class SS prediction using Conditional Neural Fields (CNFs), a recently-invented probabilistic graphical model. This CNF method not only models complex...
Structural machine learning method-covering algorithm (CA) possesses faster speed, lower complexity and higher precision. But construction of the weight of the neurons for new center of sphere domain is usually given a manmade criteria, could not follow the distribution of samples to achieve the optimal solution. In this paper, a new constructive algorithm which combines the cross covering algorithm...
This paper presents a Bangla phoneme recognition method for Automatic Speech Recognition (ASR). The method consists of three stages: i) a multilayer neural network (MLN), which converts acoustic features, mel frequency cepstral coefficients (MFCCs), into phoneme probabilities, ii) the phoneme probabilities obtained from the first stage and corresponding Δ and ΔΔ are inserted into another MLN to improve...
We propose and evaluate a framework for detection of plant leaf/stem diseases. Studies show that relying on pure naked-eye observation of experts to detect such diseases can be prohibitively expensive, especially in developing countries. Providing fast, automatic, cheap and accurate image-processing-based solutions for that task can be of great realistic significance. The proposed framework is image-processing-based...
The selection of a particular neural network model belonging to the Pareto front is a problem that exists in all multi-objective algorithms. This paper proposes a novel solution to this problem based on a linear combination of the outputs of the two extremes in the Pareto front, which form an ensemble. The decision support TOPSIS method is used to determine which linear combination creates the best...
Image thresholding is a very important phase in the image analysis process. However, different images have different characteristics making the traditional process of thresholding by one algorithm a very challenging task. That is because any thresholding method may be perform well for some images but for sure it will not be suitable for all images. In this paper, intelligent thresholding by training...
In this paper, an image similarity matching retrieval algorithm based on synergetic neural network (SNN) is proposed. It is a novel method with advantages of no pseudo-state and closer to natural self-organization process in the field of image retrieval. It utilizes feature vector extraction, attention parameter selection, order parameter calculation, pseudo-inverse matrix and its determinant value...
In this paper we present a new method for nonlinear compensation of mismatches, e.g. additive noise, on clean and noisy speech recognition. We were inspired by the human recognition system in development and implementation of a new Bidirectional Neural Network (BNN). This procedure, results in improvement of input features and consequently increasing the overall recognition accuracy. The feedforward...
Recent studies on the geometry of fractals indicate that tumors with irregular shapes can be utilized for the study of the morphology and diagnosis of cancerous cases. In this paper, we deal with the fractal modeling of the mammographic images and their background morphology. It is shown that the use of fractal modeling as applied to a given image can clearly discern cancerous zones from noncancerous...
The rapid development of automobile industry in China promotes the stable growth of the automotive aftermarket. For optimizing supply chain operations and reducing costs, it is critical for a company to forecast the demands for auto spare parts in the future. This paper proposes an improved Regression-Bayesian-BBNN (RBBPNN) based model to realize the demands forecasting. Compared with a classic ARMA...
A novel Neural Network Based Fuzzy Inference System for financial default forecast will be introduced. A wide range of financial forecasts is known. This method is focusing on the economical default forecast, but the method can be used generally for other financial forecasts as well, for example for calculating the Value at Risk. This hybrid method is combined by two classical methods: the artificial...
DDoS attack is a major Internet security problem-DoS is that lots of clients simultaneously send service requests to certain server on the internet such that this server is too busy to provide normal services for others. Attackers using legitimate packets and often changing package information, so that traditional detection methods based on feature descriptions is difficult to detect it. This paper...
In order to improve the Vehicle Weigh in Motion System with precision, the paper introduces Nerve Net Algorithm to error analysis. The article sets up a neural network model by determining the neural network input and output variables. Then, the function is defined by net training on MATLAB software. Finally through the experimental verification of Nerve Net Algorithm improving Weigh in Motion System...
Vietnamese is the national and official language in Vietnam. In the Vietnamese writing system, most of vowels have diacritical signs. With this special feature, secret information can be embedded into Vietnamese documents by slightly shifting up/down and left/right these signs. The embedded documents are nearly the same as the original ones, and so the reader could not find any differences by eyes...
This paper presents a new approach for breast cancer diagnosis using a combination of an Adaptive Network based Fuzzy Inference System (ANFIS) and the Information Gain method. In this approach, the ANFIS is to build an input-output mapping using both human knowledge and machine learning ability and the information gain method is to reduce the number of input features to ANFIS. An experimental result...
This paper provides a method of discriminate analysis based on artificial neural network (ANN). 2-Class and multi-class discriminant analysis are separately discuss using Back Propagation network. The results of our study indicate that discriminate analysis based on ANN could classify the observation more accurately than the traditional methods.
The survival and development of human being are seriously threatened by the decrease of nature forest in all over the world. As a result, it has been widely focused on the intensive farming of plantation and scientific utilization of wood resource. The characteristics of regression analysis method, time series method and neural network method commonly used in wood quality forecast were analyzed. The...
The paper deals with the design and development of classifiers and, in particular, with the problem of selecting the most relevant input variables to be used as inputs for classification purpose in practical applications. In many real problems the selection of input variables is a very important task: often real datasets used for developing a classifier contain a high number of inputs but no a priori...
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