[PDF] Top 20 NEURAL NETWORK APPROACH FOR EYE DETECTION

NEURAL NETWORK APPROACH FOR EYE DETECTION

... on eye-blink count and eye directed instruction controlhelps the driver to prevent from collision caused by drowsy ...driving. Eye detection and tracking under various conditions such as ... See full document

13

Early Detection of Lung Cancer Using Neural Network Techniques

... nodule detection scheme with accuracy of ...hybrid approach is presented in the paper [27] which is a combination of image processing and data mining ...Computer-Aided Detection (CAD) scheme in [30] ... See full document

6

A Technique for Pulse RADAR Detection Using RRBF Neural Network

... MLP network for pulse radar detection to suppress the unwanted ...RNN approach which yielded better SSR than MLP and autocorrelation approach is reported in ...RBF network which ... See full document

6

Automatic volcanic ash detection from MODIS observations using a back-propagation neural network

... In addition to human health impacts, such as eye irritation and respiratory stress (Langmann, 2013), volcanic ash poses a serious threat to the aviation industry. Ash can melt onto the jet engine turbine and lead ... See full document

9

A hybrid end-to-end approach integrating conditional random fields into CNNs for prostate cancer detection on MRI

... PCa detection methods on multiparametric Magnetic Resonance Imaging (mpMRI) are still a compelling ...Deep Neural Network architecture is developed for the task of classifying clinically significant ... See full document

19

A fast neural-dynamical approach to scale-invariant object detection

... dynamical neural network which binds compatible features together by employing a Bayesian criterion and a set of previously observed object ...evaluating detection performance on a dataset of common ... See full document

8

A RECURRENT ELMAN NEURAL NETWORK - BASED APPROACH TO DETECT THE PRESENCE OF EPILEPTIC ATTACK IN ELECTROENCEPHALOGRAM (EEG) SIGNALS

... Elman Neural Network by using a time frequency domain characteristics of EEG signal called Approximate Entropy ...Elman neural network. This proposed system proposes a ... See full document

4

AN ANN APPROACH FOR NETWORK INTRUSION DETECTION USING ENTROPY BASED FEATURE SELECTION

... the network. This has led to the research area of intrusion detection which essentially analyzes the network traffic and tries to determine normal and abnormal patterns of ...some neural ... See full document

15

HYBRID OF FUZZY CLUSTERING NEURAL NETWORK OVER NSL DATASET FOR INTRUSION DETECTION SYSTEM

... intrusion detection dataset because of the inherent ...for network-based IDSs, but (Tavallaee et ...intrusion detection methods instead of using the random ... See full document

13

A 2D Hopfield Neural Network approach to mechanical beam damage detection

... field Neural Network for online damage detection in beams subjected to external ...damage detection can be associated to an identification prob- ...Hopfield Neural Network uses ... See full document

15

Automatic eye localization in color images

... face detection and eye localization using neural network for color ...decision-based neural network (SPDNN) is used to learn the conditional distribution for each color ...by ... See full document

8

Disease Detection of Cotton Leaves Using Advanced Image Processing

... human eye cannot differentiate minute variation in color symptoms, various identifying techniques are ...propagation neural network can be used for features extraction and those features are used to ... See full document

7

Automatic detection of thermal damage in grinding process by artificial neural network

... This work aims to develop an intelligent system for detecting the workpiece burn in the surface grinding process by utilizing a multi-perceptron neural network trained to generalize the process and, in ... See full document

6

Nodules Segmentation in Breast Ultrasound using the Artificial Neural Network Self-Organizing Map

... Aware of this, screening techniques which allow early diagnosis and treatment have been studied in order to increase the chances of survival, using less aggressive treatment [1], [3]. Currently, mammography is the ... See full document

4

Survey on Various Gesture Recognition Techniques for Interfacing Machines Based on Ambient Intelligence

... Eyes and Nose are the most salient and robust features on human faces. The precise detection of eyes and the nose tip had been a crucial step in many face-related applications. A handful of hardware solutions came ... See full document

12

Short-term electricity prices forecasting in a competitive market: A neural network approach

... Multilayer perceptrons are the best known and most widely used kind of neural network. Networks with interconnections that do not form any loops are called feedforward. Recurrent or non-feedforward networks ... See full document

8

Threshold Prediction of a Cyclostationary Feature Detection Process using an Artificial Neural Network

... The number of inputs in the input layer depends on the number of inputs we use in an actual system which is to be realized by an ANN. There can be any number of hidden layer and each hidden layer may contain any number ... See full document

8

Speed Estimation of Adaptive Fuzzy-Controlled Piezo-Electric Motor using MLP-Neural Network

... The first model was proposed in 1943 by W.S. Mc Culloch and W. Pitts. The latter supposed that the nervous impulse was the expression or the result of a simple calculation carried out by each neuron and that it is thanks ... See full document

4

Fighting Botnets - A Systematic Approach

... The network modeling framework is a multistage space state process able to model the number of error or alert messages and the different states of the network in terms of security ... See full document

8

A system for improving fall detection performance using critical phase fall signal and a neural network

... a neural network can distinguish falls from ...a neural network in this study is better than that from the support vector machine shown in our previous work (Jantaraprim et ... See full document

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