The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
An Artificial Neural Network (ANN) is a statistical data modeling tool inspired by the functionality and the structure of the biological nervous system. An ANN consists of processing elements known as neurons that are interconnected to each other and work in unison to answer a particular problem. Neural networks can be used in places where detecting trends and extracting patterns are too complex to...
An efficient and flexible dictionary designing algorithm is proposed for sparse and redundant signal representation. The proposed Augmented Dictionary (AD) is based on a new dictionary model with an augmented form compared to the conventional model. With this model, we can bridge the gap between the classic dictionary learning approaches, which have general structure yet lack computational efficiency,...
Classification of signals acquired by condition monitoring systems for automotive application is becoming increasingly important. The work presented in this paper is motivated by a real-life classification challenge organized by Ford. Data samples from an automotive subsystem were collected. A classifier is designed to robustly isolate the different types of problems, by analyzing the acquired signals...
Data mining approaches have been used in business purposes since its inception; however, at present it is used successfully in new and emerging areas like education systems. Government of Bangladesh emphasizes the need to improve the education system. In this research, we use data mining approaches to predict students' final outcome, i.e., final grade in a particular course by overcoming the problem...
In the present paper we describe a recent approach of probabilistic self-organizing maps (PRSOM). The PRSOM become more and more interesting in many fields such as: pattern recognition, clustering, classification, speech recognition, data compression, medical diagnosis… The PRSOM give an estimation of the density probability function of the data, this density dependent on the parameters of the PRSOM,...
Marathi is one of the ancient Indian languages majorly spoken in the state of Maharashtra. Marathi is one of the Devanagari script and the literals and numerals are almost similar to Hindi. Recognition of handwritten Marathi numerals is quite challenging task because people have the practice of writing these numerals in variant ways. In this work we have presented a method to recognize the handwritten...
Many systems have been developed for computer analysis of the lungs in high resolution computed tomography (HRCT) scans for detection and analysis of Interstitial Lung Diseases (ILDs). This paper presents a novel approach for classification of lung tissue patterns affected with Interstitial Lung Diseases (ILDs) in high resolution computed tomography (HRCT) scans. The proposed scheme makes use of texture...
Ensembles of neural networks have been the focus of extensive studies over the past two decades. Effectively encouraging diversity remains a key element in yielding improved performance from such ensembles. Negatively correlated learning (NCL) has emerged as a promising framework for concurrently training an ensemble of learners while emphasizing the cooperation among them. The NCL methodology relies...
This paper analyzes different spatial distribution of the field strength in the far field of different antenna. We will receive the field strength in the same area by receiving array based on directional diagram, and then send the data to BP neural network to simulate the nonlinear features of different antenna modeling so as to achieve the classification of different antenna. At last we will compare...
An active under-sampling approach is proposed for handling the imbalanced problem in this paper. Traditional classifiers usually assume that training examples are evenly distributed among different classes, so they are often biased to the majority class and tend to ignore the minority class. in this case, it is important to select the suitable training dataset for learning from imbalanced data. the...
In order to realize automatically classifying can defects and improve the convergence speed and the classification accuracy of Self-Organizing Feature Map (SOFM) neural network, 5 improved measures are presented in this paper. They include using typical sample vector, introducing frequency sensitive factor, learning rate adaptive adjustment, selecting convergence criterion and searching winning neuron...
This paper presents the design and implementation of a machine learning based activity classification mechanism for hens using a wearable sensor system. Legislation and social demands in the U.S. and Europe are pushing the poultry industry towards the usage of non-cage housing systems. However, non-cage systems typically house hens in groups of hundreds or thousands, which makes it nearly impossible...
In this investigation, a cancer classification approach is presented using clustering based gene selection and artificial neural networks. To address the so called ‘curse of dimensionality’ a T-statistic feature selection method, one of the univariate filter techniques, is used to select the most informative genes. However, instead of selecting a small group of relevant genes at once from the whole...
Optical character recognition (OCR) is a popular research topic in artificial intelligent area. One of the most important parts of OCR is word recognition. So in this paper, we propose a combination method of selected subsets of Zernike features and MLP Back-Propagation Neural network to recognize Persian words. These words are the most useful and common words among 1000 words in Persian handwritings...
Attracting more students into science and engineering disciplines concerned many researchers for decades. Literature used traditional statistical methods and qualitative techniques to identify factors that affect student retention up most and predict their persistence. In this paper we developed two neural network models using a feed-forward backpropagation network to predict retention for students...
In this paper, Probabilistic Neural Network with image and data processing techniques was employed to implement an automated brain tumor classification. The conventional method for medical resonance brain images classification and tumors detection is by human inspection. Operator-assisted classification methods are impractical for large amounts of data and are also non-reproducible. Medical Resonance...
This paper presents a comparison of 1-nearest neighbour (1-NN) and neural network based classification of patient activity. The data for classification was acquired from two 6 degree-of-freedom accelerometers deployed at the wrists of a patient. Instead of calculating statistical values, we studied the use of data samples acquired from 200ms time window. The best results were achieved with the 1-nearest...
In this paper, we present a model based on the Neural Network (NN) for classifying Arabic texts. We propose the use of Singular Value Decomposition (SVD) as a preprocessor of NN with the aim of further reducing data in terms of both size and dimensionality. Indeed, the use of SVD makes data more amenable to classification and the convergence training process faster. Specifically, the effectiveness...
Digital image processing is a rapidly growing area of computer science since it was introduced and developed in the 1960's. In the case of flower classification, image processing is a crucial step for computer-aided plant species identification. Colour of the flower plays very important role in image classification since it gives additional information in terms of segmentation and recognition. On...
Speech production and speech phonetic features gradually improve in children by obtaining audio feedback after cochlear implantation or using hearing aid. In this study, voice disorders in children with cochlear implantation and hearing aid are classified. 30 Persian children participated in the study, including 6 children in levels 1 to 3 and 12 in level 4. Voice samples of 5 isolated Persian words...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.