نتایج جستجو برای: ann classifier
تعداد نتایج: 68429 فیلتر نتایج به سال:
In order to classify different human brain states related to visual perception of ambiguous images, we use an artificial neural network (ANN) to analyze multichannel EEG. The classifier built on the basis of a multilayer perceptron achieves up to 95% accuracy in classifying EEG patterns corresponding to two different interpretations of the Necker cube. The important feature of our classifier is...
We report a pilot study designed to test elastic light-scattering (ELS) spectroscopy for characterizing normal, tumor, and tumor-infiltrated brain tissues. ELS spectra were measured from 393 sites on 36 ex vivo tissue specimen obtained from 29 patients. We employed and compared the performances of three methods of spectral classification for tissue characterization, including spectral slope ana...
Sign Language Recognition (SLR) is the most structured field in gesture recognition applications, such that each gesture has assigned a well-defined meaning. SLR can be defined as a translation system, which translates the signs, performed by deaf and dump people to the natural language. The proposed system aims to recognize Arabic sign language (ASL) and converts it to the natural Arabic langu...
Artificial intelligence is integral part of a neural network is based on mathematical equations and artificial neurons. The focus here is the implementation of the Artificial Neural Network Architecture (ANN) with on chip learning in analog VLSI for pattern recognition. It is a maximum likelohood classifier which can be implemented using VLSI. Modified Hamming neural network architecture is pre...
Accurate biometric system for authentication is the need of the hour in today’s scenario. In face spoofing attack a person tries to pretend to be a valid user by using photo or video of an authorized person and gets illegitimate access. Hence it is essential to develop a robust and authentic face spoof detection system in order to protect the privacy about the person. Centre of attraction of th...
A new intelligent segmentation technique is proposed that may be used in conjunction with a neural classifier and a simple lexicon for the recognition of difficult handwritten words. A heuristic segmentation algorithm is initially used to over-segment each word. An Artificial Neural Network (ANN) trained with 32,034 segmentation points is then used to verify the validity of the segmentation poi...
This paper presents an improvement of classification performance for electroencephalography (EEG)-based driver fatigue classification between fatigue and alert states with the data collected from 43 participants. The system employs autoregressive (AR) modeling as the features extraction algorithm, and sparse-deep belief networks (sparse-DBN) as the classification algorithm. Compared to other cl...
Previous evidence showed a 75.5% best accuracy in the classification of 120 Alzheimer's disease (AD) patients with dementia and 100 matched normal elderly (Nold) subjects based on cortical source current density and linear lagged connectivity estimated by eLORETA freeware from resting state eyes-closed electroencephalographic (rsEEG) rhythms (Babiloni et al., 2016a). Specifically, that accuracy...
This paper presents the use of Artificial Neural Networks (ANN) as a pattern classifier for the combined differential protection of generator-transformer unit with an aim to build a backup protection system to improve the overall reliability of the system. The proposed neural network model is trained and tested with an efficient Resilient Back propagation (RPROP) algorithm and Genetic Algorithm...
Due to the recent trend of technologies to use the network based systems, detecting them from threats become a crucial issue. This paper investigates applying the following methods to detect the attacks in network: Genetic Algorithms (GA) with Artificial Neural Networks classifier, Modified Mutual Information Feature selection (MMlFS), Linear Correlation Feature Selection (LCFS), and Forward Fe...
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