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.
We compare the performance of multilayer perceptrons (MLPs) obtained using back propagation (BP), decision boundary making (DBM) algorithm and extreme learning machine (ELM), and investigate better method for developing aware agents (A-agent) that are suitable for implementation in portable/wearable computing devices (P/WCD). The DBM has been proposed by us for inducing compact and high performance...
With the continuous development of network and database technology, share and conversion on heterogeneous data are still a complex problem currently facing. Current methods are mostly based on the similarity between the field to complete the matching process, although this method can finish partial matches on information, its time complexity is very high due to the large processing data sets and the...
Because of the shortage for automatic straightening of the elevator guide rail based on database, this paper proposes the design method for that based on neural network. A neural network was built for the automatic straightening process of the elevator guide rail with the initial bending value and the supporting points span as the input parameters, the straightening exceeded value as the output parameter...
the objective to develop clinical decision support system (CDSS) tools is to help physicians making faster and more reliable clinical decisions. The first step in their development is choose a machine learning classifier as the system core. Previous works reported implementation of artificial neural networks, support vector machines, genetic algorithms, etc. as core classifiers for CDSS; however,...
This paper presents an attempt to solve the challenging problem of Devanagari numeral and character recognition. It uses structural and geometric features to represent the Devanagari numerals and characters. Each image is zoned in 9 blocks and 8 structural features are extracted from each block. Similarly 9 global geometric features are extracted. These 81 features are used for representing the image...
In textile industry, the quality of fabrics is a very important factor of competitiveness given that defects have a negative effect on the market value of the product. For this raison, it is necessary to master good quality fabric rolls from the looms. Typically, the fabric inspection is performed by a human controller that uses a display system and relies on personal knowledge. The objective of our...
This paper discusses signature verification and recognition using a new approach that depends on a neural network which enables the user to recognize whether a signature is original or a fraud. The user introduces into the computer the scanned images, modifies their quality by image enhancement and noise reduction techniques, to be followed by feature extraction and neural network training, and finally...
Through in-depth study on the existing technologies about intrusion detection system, to accelerate the detection speed and improve the accuracy, this paper presents a new intrusion detection model based on neural networks. This model uses neural networks to detect, transforms the pattern recognition into numerical calculation, thereby speeding up the detection rate, while combining with expert system...
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.