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International Conference on Neural Networks and Artificial Intelligence: Recent submissions
Now showing items 21-40 of 77
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A weighting function approach for neural network nonlinear time series analysis of satellite remote sensing of rainstorms
(BrSTU, 2006)One of frequently used neural networks, i.e., a radial-based function network (RBFN) with Gaussian activation functions is employed to study the nonlinear time series by carrying out the characterization experiments for a GMS- 5 satellite 11 µm IR observations of rainstorm process. The proposed ...2023-11-27
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Neural Networks for Chaotic Signal Processing: Application to the Electroencephalogram Analysis for Epilepsy Detection
(BrSTU, 2006)Many techniques were used in order to detect and to predict epileptic seizures on the basis of electroencephalograms. One of the approaches for the prediction of epileptic seizures is the use the chaos theory, namely determination largest Lyapunov's exponent or correlation dimension of scalp EEG ...2023-11-27
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An Approach to Interplanetary Shocks Prediction Using Single ACE/EPAM Channel Data
(BrSTU, 2006)An approach to prediction of the arrival time of interplanetary shocks using neural networks based on the data gathered from single EPAM (Electron, Proton and Alpha Monitor) channel o f NASA's ACE (Advanced Composition Explorer) spacecraft is proposed in this paper. A short description of ACE spacecraft ...2023-11-24
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View-Based Word Recognition System
(BrSTU, 2006)In this paper, a new method for word recognition and classification without segmentation is presented. The worked out algorithm is based on recognizing the whole word without separating it into letters. According to this algorithm, entire words are treated and analyzed as object images subject to ...2023-11-24
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Resampling-down Mesh based Discriminant Filter Synthesis for Face Recognition
(BrSTU, 2006)Presented paper addresses face recognition algorithm by means o f synthetic discriminant filters synthesized in pseudo 3-D mesh domain. The objective of the research is to construct facial descriptor in the form of linear filter, which should produce high and low outputs for intra- and inter-class ...2023-11-24
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A Neural Network Based Speech Recognition System For Isolated Tamil Words
(BrSTU, 2006)Speech recognition is always looked upon as a fascinating field in human computer interaction. It is one of the fundamental steps towards understanding human cognition and their behavior. White most of the literature on speech recognition is based on Hidden Markov Models (HMM). This paper presents a ...2023-11-24
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An Approach to Solving Face Detection Task
(BrSTU, 2006)In this paper a pattern-recognition based approach to solving face detection task is proposed. All main steps are revealed and algorithms for their solution are built. It is shown that these algorithms in the aggregate effectively solve the face detection task. The conditions when the exact solution ...2023-11-24
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A Framework for Parallel Processing of Image Dataflow in Industrial Applications
(BrSTU, 2006)Basic algorithms and processing technologies of integrated circuit layout images are considered. The images represented as a set of frames can regard as a dataflow and the processing are perfectly suited for parallel implementation. Framework architecture for designing parallel systems of image dataflow ...2023-11-24
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Image Representation Based Hybrid Intelligent Diagnosis Approach for Computer Aided Diagnosis (CAD) Systems
(BrSTU, 2006)Computer Aided Diagnosis (CAD) is one of the most interesting and most difficult dilemma dealing in one hand with expert (human) knowledge consideration. On the other hand, fault diagnosis is a complex and fuzzy cognitive process and soft computing approaches as modular neural networks and fuzzy logic, ...2023-11-24
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Comparative Analysis of Neural Networks and Statistical Approaches to Remote Sensing Image Classification
(BrSTU, 2006)This paper examines different approaches to remote sensing images classification. Included in the study are statistical approach, namely Gaussian maximum likelihood classifier, and two different neural networks paradigms: multilayer pcreeptron trained with EDBD algorithm, and ARTMAP neural network. ...2023-11-24
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Learning From The Environment With A Universal Reinforcement Function
(2006)Traditionally, in Reinforcement Learning, the specification of the task Ls contained in the reinforcement function (RF), and ach new task requires the definition of a new RF. But in the nature, explicit reward signals are limited, and the characteristics of the environment afTects not only how animals ...2023-11-23
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Can neural networks holistically reprogram themselves through their own observation?
(BrSTU, 2006)Neural networks (NNs) are inspired -at least metaphorically -from biological solutions nature selected by evolution. On one hand, learning algorithms' efficacy has been widely demonstrated experimentally, even if the mathematical proof of their convergence is not always very easy to establish (SOM). ...2023-11-23
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Five Strategies of the Self-Tutoring of a Neural Networks by E. Sokolov
(BrSTU, 2006)The bionic models of neural networks are of interest. A bionic model that suggested by Prof. E. Sokolov consisting of detectors and control neurons. In his model the self-tutoring is designed, the environment and a purpose of neural network's behaviour are considered. In this article five various ...2023-11-23
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Classification of handwritten signatures based on boundary tracing
(BrSTU, 2006)The paper presents a system for offline classification of handwritten signatures. The algorithm is based on boundary tracing technique for extracting characteristic features. Outer and inner boundaries are treated separately. The upper and lower parts of the boundaries are extracted to form two sequences ...2023-11-23
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A Modification of the FCM-CV-algorithm and Its Application for Radar Portraits Classification
(BrSTU, 2006)Sadowska, K. A Modification of the FCM-CV-algorithm and Its Application for Radar Portraits Classification / K. Sadowska A. Sharamet // International Conference on Neural Networks and Artificial Intelligence : proceedings, Brest, 31 May – 2 June, 2006 / Edited: V. Golovko [et al.]. – Brest : BSTU, ...2023-11-23
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On the Inspection of Classification Results in the Fuzzy Clustering Method Based on the Allotment Concept
(BrSTU, 2006)Viattchenin, Dmitri A. On the Inspection of Classification Results in the Fuzzy Clustering. Method Based on the Allotment Concept / Dmitri A. Viattchenin // International Conference on Neural Networks and Artificial Intelligence : proceedings, Brest, 31 May – 2 June, 2006 / Edited: V. Golovko [et al.]. ...2023-11-23
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International Conference on Neural Networks and Artificial Intelligence
(BrSTU, 2006)This book collected the papers of the 4th International Conference on Neural Networks and Artificial Intelligence. They are arranged in following streams: Cyberspace Security and Defense, Neural Robotics, Neural Diagnosis, Neural Prediction, Pattern Recognition, Image Processing, Pattern Classification. ...2023-11-23
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International Conference on Neural Networks and Artificial Intelligence ICNNAI’99 = Международная конференция по нейронным сетям и искусственному интеллекту ICNNAI’99
(BPI, 1999)International Conference on Neural Networks and Artificial Intelligence ICNNAI’99 = Международная конференция по нейронным сетям и искусственному интеллекту ICNNAI’99 : proceedings, Brest, Belarus, 12–15 October 1999 / Brest Polytechnic Institute, Department of Computers and Laboratory of Artificial ...2021-07-27
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Methods of Partial Logic
(BPI, 1999)This paper presenls novel theoretical results obtained in the field of partial logie. New operations (including a very useful minimization operation), laws, and expansions are introduced. Traditional Boolean function representation forms for the completely specified functions are generalized for the ...2021-07-27
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Determination of Features of the Dependence of Neuron Net Output Coordinates on Other Coordinates and Parameters of Neuron Net
(BPI, 1999)The paper presents the deduction of main relationships of back-propagation algorithm on the basis of approximation of the unknown dependence of the efficiency factor on neural net parameters by the linear part of Taylor series. Such an approach for deduction of known results is intended to relax the ...2021-07-27