• No results found

[PDF] Top 20 Robust Iris Classification Based on Deep Neural Network (DNN) and Stationary Wavelet Transform (SWT)

Has 10000 "Robust Iris Classification Based on Deep Neural Network (DNN) and Stationary Wavelet Transform (SWT)" found on our website. Below are the top 20 most common "Robust Iris Classification Based on Deep Neural Network (DNN) and Stationary Wavelet Transform (SWT)".

Robust Iris Classification Based on Deep Neural Network (DNN) and Stationary Wavelet Transform (SWT)

Robust Iris Classification Based on Deep Neural Network (DNN) and Stationary Wavelet Transform (SWT)

... CASIA Iris database and the results obtained from the proposed model shows superior results with recognition rate of ...combining Iris, Palmprint, and ...right iris where further encoding procedure ... See full document

7

Multimodal MRI-based classification of migraine: using deep learning convolutional neural network

Multimodal MRI-based classification of migraine: using deep learning convolutional neural network

... In recent years, resting-state functional magnetic resonance imaging (rs-fMRI) has attracted considerable attention for studying neural mechanisms. This approach not only overcomes the potential limitation ... See full document

14

Content Based Image Retrieval and Classification Using Image Features and Deep Neural Network

Content Based Image Retrieval and Classification Using Image Features and Deep Neural Network

... Content based image retrieval is a challenging method of capturing relevant images from a large storage ...content based image retrieval depends on features, feature extraction techniques, similarity ... See full document

7

Robust Neural Network Classifier

Robust Neural Network Classifier

... - Classification is a data mining technique used to predict Patterns’ ...Pattern classification involves building a function that maps the input feature space to an output space of two or more than two ... See full document

6

Development of a deep neural network for automated electromyographic pattern classification

Development of a deep neural network for automated electromyographic pattern classification

... in classification but is unable to account for the high signal variability present in sEMG, which led to a substantial decrease in ...sEMG classification task and accounts for this inherent signal ... See full document

5

Mammographic breast density classification using a deep neural network: assessment based on inter-observer variability

Mammographic breast density classification using a deep neural network: assessment based on inter-observer variability

... convolutional neural network can provide labeling comparable to an average ...a deep learning algorithm for a subjective classification task with caution and hypothesize that the best way to ... See full document

7

Review of Deep Neural Network Based on Auto encoder

Review of Deep Neural Network Based on Auto encoder

... vector based on the interference, and the input vector after decoding is required to keep the original information as much as ...the network is very robust to the input ... See full document

8

Deep Learning Pre-Trained Architecture Of Alex Net And Googlenet For DICOM Image Classification

Deep Learning Pre-Trained Architecture Of Alex Net And Googlenet For DICOM Image Classification

... Abstract: Deep learning is a subset of machine learning and it is dedicated to the development of machines which would learn based on the given inputs and eventually attaining Artificial Intelligence ... See full document

7

Deep Markov Neural Network for Sequential Data Classification

Deep Markov Neural Network for Sequential Data Classification

... a Deep Markov Neu- ral Network (DMNN) for incorporating sequential data and arbitrary features into language model- ...current neural networks, such as the vanishing gra- dient ... See full document

6

Deep neural network models for image classification and regression

Deep neural network models for image classification and regression

... technique based on the Bandelet transform and the multiscale geometrical ...those based on multitemporal prediction ...prediction based on the expectation-maximization (EM) algorithm and the second ... See full document

98

A Novel Method for Remotely Sensed Hyperspectral Image Classification
Based on Convolutional Neural Network

A Novel Method for Remotely Sensed Hyperspectral Image Classification Based on Convolutional Neural Network

... image classification is the process of assigning land cover classes to ...and classification approaches affect the success of ...Convolutional Neural Networks (CNN) are gaining attention due to their ... See full document

10

Disease Detection in the Leaves of Multiple Plants

Disease Detection in the Leaves of Multiple Plants

... The deep algorithms can be made useful in plant disease ...a deep learning based method for the detection of diseases effected in the leaves of ...the deep Convolutional Neural ... See full document

5

DEEP NEURAL CLASSIFICATION AND LOGIT REGRESSION BASED ENERGY EFFICIENT ROUTING 
IN WIRELESS SENSOR NETWORK

DEEP NEURAL CLASSIFICATION AND LOGIT REGRESSION BASED ENERGY EFFICIENT ROUTING IN WIRELESS SENSOR NETWORK

... priority based on the usage and the availability of the power base on SOC of the battery leading to a total load reduction so that there will be energy at all time and avoid deep discharging of the battery ... See full document

10

DEEP NEURAL CLASSIFICATION AND LOGIT REGRESSION BASED ENERGY EFFICIENT ROUTING 
IN WIRELESS SENSOR NETWORK

DEEP NEURAL CLASSIFICATION AND LOGIT REGRESSION BASED ENERGY EFFICIENT ROUTING IN WIRELESS SENSOR NETWORK

... Hence based on our research [3], the criticality level of an emergency condition of pilgrims is identified by the vital signs, threshold values and data rate of related health ... See full document

12

DEEP NEURAL CLASSIFICATION AND LOGIT REGRESSION BASED ENERGY EFFICIENT ROUTING 
IN WIRELESS SENSOR NETWORK

DEEP NEURAL CLASSIFICATION AND LOGIT REGRESSION BASED ENERGY EFFICIENT ROUTING IN WIRELESS SENSOR NETWORK

... antenna network by applying heuristics data like bit-error rates, to discriminate jamming from regular ...the network topology change can track mobile ... See full document

11

DEEP NEURAL CLASSIFICATION AND LOGIT REGRESSION BASED ENERGY EFFICIENT ROUTING 
IN WIRELESS SENSOR NETWORK

DEEP NEURAL CLASSIFICATION AND LOGIT REGRESSION BASED ENERGY EFFICIENT ROUTING IN WIRELESS SENSOR NETWORK

... From figure 7, it is clearly observed that the energy consumption is significantly reduced using EEDNC-LRR technique. This is because, the energy efficient deep neural classifier calculates the energy and ... See full document

15

VDCNN based Noise Robust Speech Recognition with Combination of GMM and MFCC Features

VDCNN based Noise Robust Speech Recognition with Combination of GMM and MFCC Features

... Very Deep Convolutional Neural Networks (CNNs) for strong speech ...very deep CNNs in the field of computer vision, where image classification has enhanced to extraordinary degree by growing ... See full document

9

The Unsupervised Gravitational Mass Weighted Probability PCA For Pixel-Wise And Sub-Pixel Wise Classification

The Unsupervised Gravitational Mass Weighted Probability PCA For Pixel-Wise And Sub-Pixel Wise Classification

... samples. Based on the neighborhood information the unlabeled samples and labeled information are ...the deep Convolutional neural network with sparse representation to extract the deep ... See full document

11

Relation Classification via Convolutional Deep Neural Network

Relation Classification via Convolutional Deep Neural Network

... ing Deep Learning to learn features. In NLP, such methods are primarily based on learning a distributed representation for each word, which is also called a word embeddings (Turian et ...recursive ... See full document

10

Deep convolutional neural network based medical image classification for disease diagnosis

Deep convolutional neural network based medical image classification for disease diagnosis

... image classification and the particular challenge of the medical image-small dataset, this paper chose to study how to apply CNN-based clas- sification to small chest X-ray dataset and evaluate their ... See full document

18

Show all 10000 documents...