[PDF] Top 20 Static Gesture Recognizer Using Hybrid Neural Network
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Static Gesture Recognizer Using Hybrid Neural Network
... employing Hybrid Neural Network (NN) for an Efficient Static ...The Hybrid Neural Network consists of Active Contour Model (ACM) and Convolutional Neural ... See full document
6
Gesture Recognition of RGB and RGB-D Static Images Using Convolutional Neural Networks
... on gesture recognition for different purposes, some focusing on the whole body [6] while others focusing on a specific part as eyes [7] or hands ...[9]. Gesture recognition can be classified into two ... See full document
6
A Neural Network based Real Time Hand Gesture Recognition System
... hand gesture recognition based on different methods and ...Hand Gesture Recognition Using Computer Vision developed by Ray Lockton [2] in which he build a man-machine interface using a video ... See full document
6
ARTIFICIAL NEURAL NETWORK APPROACH FOR HAND GESTURE RECOGNITION
... hand gesture recognition using visual analysis have been proposed for hand gesture ...same using Input-output Hidden Markov Models ...hand gesture recognition using depth data ... See full document
6
Sign Language Recognition using Hybrid Neural Networks
... Holden et al. (2001) presented the hand tracker which includes 3D hand alignment with number of degree-of-freedoms (DOFs) from 2D image sequence with a color coded glove. Furthermore, the adaptive fuzzy expert system is ... See full document
7
MOUSE NAVIGATION CONTROL USING HAND GESTURE WITH NEURAL NETWORK
... a listof descriptions, or a ' feature vector [17]. For posture recognition, (static hand gestures) features such as fingertips, finger directions and hand’s contours can be extracted. Features are thus selected ... See full document
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PATTERN MATCHING ALGORITHM FOR ASL SIGN GESTURE RECOGNITION USING NEURAL NETWORK
... for static symbol recognition and translation of ...hand gesture for ASL, because it is fast and simple ...By using this approach we can recognize gestures having open as well as closed fingers more ... See full document
10
Hand & Upper Body Based Hybrid Gesture Recognition
... by using expressive movements like gestures and postures is much ...6 gesture classes are recognized during the testing process of this approach and neural network is used for ... See full document
5
Static Gesture Recognition of Devnagari Sign Language using Feed Forward Neural Network
... Language Using Feed forward Neural ...sets gesture images were used and the remaining 6 sets were used for ...to Using Histogram technique and work get misclassified ...recognition ... See full document
5
HAND GESTURE RECOGNITION USING NEURAL NETWORK
... the static along with dynamic gestures over a period of ...called gesture recognition.The aim of gesture recognition is tocreate a system which can analyzespecific human gesturesand use them to ... See full document
5
Hand Gesture Recognition Using Neural Network
... categories: static and dynamic. A static gesture is a particular hand configuration and pose, represented by a single ...dynamic gesture is a moving gesture, represented by a sequence ... See full document
8
Speech Enhancement Using Neural Network
... J, W. , Multichannel Multi-tap Signal Separation By Output Decorrelation,Cambridge University, CUED/ F-INFENG/TR 250, ISSN 0951-9211 (1996). 12. Cichocki, A., Amari, S, I., and Cao, J. Blind Separation of Delayed and ... See full document
5
Self organizing map and least square support vector machine method for river flow modelling
... Hydrology data such as flows and rainfall are the basic information used in the design of the water resources system. Knowledge about the characteristics and volume of river flow is very important, especially for ... See full document
45
A NEW SOFT SET BASED PRUNING ALGORITHM FOR ENSEMBLE METHOD
... The architecture of fusion discrete wavelet transforms of the canny and morphological operations in video sequences shown in figure 2. The hand and head segmentation outputs are given to next processing of signs. The ... See full document
11
NeuroSVM: A Graphical User Interface for Identification of Liver Patients
... Artificial Neural Network, Bagging, Boosting, Naïve Bayes, Kernel-based classifiers, Nearest Neighbour algorithm, Decision Trees, Random Forest, and other ensemble of ... See full document
5
Fast and Robust Method for Dynamic Gesture Recognition Using Hermite Neural Network
... online gesture training for different users or new gestures because they focus on the improvement of iterative rules in network training, and can not avoid the lengthy iterative training ... See full document
6
Hybrid learning-based model for exaggeration style of facial caricature
... Brennan (2007), the first person to attempt developing a caricature generator, formalized caricature as a process of exaggerating the differences between the features of a subject face and average face. The rate of ... See full document
47
Modelling and predicting of MODIS leaf area index time series based on a hybrid SARIMA and BP neural network method
... BP neural network and a hybrid method of SARIMA-BP neural network were used for modeling and predicting MODIS LAI time ...SARIMA-BP neural network combined both SARIMA and ... See full document
7
Mencius: A Chinese Named Entity Recognizer Using Hybrid Model
... is: using InfoMap to help ME detect which character in the sentence is the first character of a location name and which characters are the remaining characters of a location ... See full document
17
Distribution Systems Reconfiguration Using Pattern Recognizer Neural Networks
... First, the distribution network data such as real and imaginary power, resistance, inductance and primary configuration are entered. Then a load flow study is done and total power loss and load balancing indices ... See full document
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