[PDF] Top 20 Facial feature processing using artificial neural networks

Facial feature processing using artificial neural networks

... These have frequently been some form of mathematical measure taken from the grey scale image such as the eigenface method used by Kirby and Sirovich [4] and the vector quantisation metho[r] ... See full document

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Artificial Intelligence Technique for Speech Recognition Based on Neural Networks

... signal processing in the absence of sufficient models lead to questions about the processes of generation signals using artificial neural networks, As a result; when building a signal ... See full document

6

Lung Cancer Detection using Digital Image Processing and Artificial Neural Networks

... The main advantages of computed tomography image have better clarity, low noise and distortion. Lung CT images are given as input. Dimensions of images are 512 × 512pixels in size with the layer thickness of 0.75 − ... See full document

14

Plant Disease Detection and Classification using Image Processing and Artificial Neural Networks

... forward neural network is an artificial neural network wherein connections between the units do not form a ...recurrent neural networks[12]. The feed forward neural network was ... See full document

6

CLASSIFYING ARABIC TEXT USING DEEP LEARNING

... of feature is a tough problem to ...geometry-oriented feature extraction for different handwritten ...image processing steps are used including image acquisition, digitization , preprocessing, ... See full document

13

Feature based 3D Object Recognition using Artificial Neural Networks

... The proposed methodology is based on extracting set of features from the 2D images which include the Affine, Zernike and Hu moments invariants to be used as inputs to train artificial ne[r] ... See full document

7

A feature based reverse engineering system using artificial neural networks

... 1999 Geometric feature recognition for Reverse Engineering using Neural Networks, International Journal of Advanced Manufacturing Technology submitted and awaiting referee panel's commen[r] ... See full document

300

Classification of Cardiovascular Disease Using Feature Extraction and Artificial Neural Networks

... To detect the Q, S and T points we used the state-machine logic algorithm to determine different peaks in ECG based on averaging and adaptive thresholds which has fluctuating characteristics in respect to the noise and ... See full document

16

Facial Expression Recognition using Gabor Wavelet

... Facial feature extraction attempts to find the most appropriate representation of the face images for ...geometric feature-based ...a feature vector obtained after processing the face ... See full document

5

Classification of Partial Discharge Measured under Different Levels of Noise Contamination

... performed. Feature extractions were performed on the PD data and used as the input data for artificial intelligence classifiers to classify cable joint defect ...results, feature extraction ... See full document

20

Determination of Corrosion Types from Electrochemical Noise by Artificial Neural Networks

... the Artificial Neural Networks (ANN) and the types of corrosion as the outputs of the ...A feature vector is extracted from each EN data ...of artificial neural networks ... See full document

13

Role of Artificial Neural Networks (ANN) in Image Processing

... Artificial neural networks (ANNs) are a form of computing inspired by the functioning of human brain and nervous system. ANNs have been used to carry out cognitive tasks performed naturally by the ... See full document

8

THE ROLE OF INFORMATION TECHNOLOGY ON THE GROWTH OF FIRMS: A VALUE ADDED ONSIDERATION

... users using the ...pages. Feature extraction and selection of best features play a key role in ...by using genetic algorithm. Using the selected features by GA, an Artificial ... See full document

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Artificial Neural Networks Based War Scene Classification using Invariant Moments and GLCM Features: A Comparative Study

... This paper discusses invariant moments and GLCM features based war scene classification using Artificial Neural Networks. The sample images are taken from the Computational Visual Cognition ... See full document

7

Feature extraction and classification of heart sound using 1D convolutional neural networks

... the feature parameters of heart sound ...by processing the received time domain signal, thereby enabling us to observe the formants and the attributes of the phonemes in the signal ...speech feature ... See full document

11

Feature selection of microarray data using genetic algorithms and artificial neural networks

... larger neural network had been used, the epoch number would have to be adjusted accordingly to achieve accurate ...by using the [2,1] architecture. However using a [1,2] or a [3] architecture ... See full document

71

System health management of safety critical systems using artificial neural networks

... values. Artificial Neural Networks (ANN) is a powerful tool in classification, prediction of different data ...the neural network, it can be used for further stages of processing like ... See full document

5

Correlation analysis and prediction of personality traits using graphic data collections

... social networks are ...information using the apparatus of artificial neural ...investigated, artificial neural networks are used as a ...convolutional neural ... See full document

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1. Diagnosing alzheimer’s disease and mild cognitive impairment with modalities: a survey

... for feature extraction and representation are Artificial Neural Networks(ANN), Recurrent Neural Networks(RNN), Recursive feature elimination, hybrid based features, ... See full document

8

Pattern Recognition Process, Methods and Applications in Artificial Intelligence

... ART neural networks can be used as an unsupervised vector ...in processing information, it has the ability to learn and memorize a large number of new concepts in a manner that does not necessarily ... See full document

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