Titlebook: Artificial Neural Networks - ICANN 2010; 20th International C Konstantinos Diamantaras,Wlodek Duch,Lazaros S. Il Conference proceedings 201

山顶可休息

Visual Shape Recognition Neural Network Using BESOM Model. First, the network is based on the BESOM model, which is a computational model of the cerebral cortex. Second, the Gabor filter, a model of a simple cell in the primary visual area, is used to calculate input features. Third, the network structure mimics the ventral visual pathway of the brain, wh

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Comparing Feature Extraction Techniques and Classifiers in the Handwritten Letters Classification Pr Analysis (PCA) and also to compare two different kinds of classifiers, Neural Networks and Support Vector Machine (SVM). To this aim, a system for handwritten letters recognition was developed, which consist of two stages: a feature extraction stage using either ICA or PCA, and a classifier based o

DEMUR

The Parameter Optimization of the Pulse Coupled Neural Network for the Pattern Recognitione defined empirically and the optimization of parameters has been known as a remaining problem of PCNN. In this study, we show a method to apply the real coded genetic algorithm to the parameter optimization of the PCNN and we also show performances of pattern recognition by the PCNN with learned pa

小淡水鱼

细颈瓶

Detecting DDoS Attack towards DNS Server Using a Neural Network Classifierthis paper we present a neural network approach to detecting the DDoS attacks towards the domain name system. A multi-layer feed-forward neural network is employed as a classifier based on the selected features that reflect the characteristics of DDoS attacks. The performance and the computational e

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Classification Based on Multiple-Resolution Data Viewters of the estimators are adjusted to minimize the classification error. We propose properties of the data for which our algorithm should yield better results than the basic version of the method. Next, we generate data with postulated properties and conduct numerical experiments. Analysis of the r

辞职

Identification of the Head-and-Shoulders Technical Analysis Pattern with Neural Networks network we use actual patterns that were identified in stochastically simulated price series by means of a rule-based algorithm. Then the patterns are being converted to binary images, in a manner similar to the one used in hand-written character and digit recognition. Our approach is tested on new

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Analyzing Classification Methods in Multi-label Tasksnnotation of images. This paper presents a comparative analysis of some existing multi-label classification methods applied to different domains. The main aim of this analysis is to evaluate the performance of such methods in different tasks and using different evaluation metrics.

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Conference proceedings 2010ng structure inspired by biolo- cal nervous systems and they consist of a large number of highly interconnected processing elements (neurons). Each neuron is a simple processor with a limited computing capacity typically restricted to a rule for combining input signals (utilizing an activation funct