A Deep Neural Network Based Optimization Approach for Wireless Resource Management

2020 ◽  
Author(s):  
Md. Habibur Rahman ◽  
Md. Munjure Mowla
Keyword(s):  
Neural Network ◽  
Resource Management ◽  
Deep Neural Network ◽  
Optimization Approach ◽  
Wireless Resource Management

Deep Neural Network for Resource Management in NOMA Networks

2020 ◽  
Vol 69 (1) ◽  
pp. 876-886
Author(s):  
Ning Yang ◽  
Haijun Zhang ◽  
Keping Long ◽  
Hung-Yun Hsieh ◽  
Jiangchuan Liu
Keyword(s):  
Neural Network ◽  
Resource Management ◽  
Deep Neural Network

scholarly journals Novel Approach of Neural Collaborative Filter by Pairwise Objective Function with Matrix Factorization

2018 ◽  
Vol 7 (3.12) ◽  
pp. 1213
Author(s):  
Ram Sethuraman ◽  
Akshay Havalgi
Keyword(s):  
Neural Network ◽  
Objective Function ◽  
Matrix Factorization ◽  
Gradient Descent ◽  
Deep Neural Network ◽  
Cross Entropy ◽  
Optimization Approach ◽  
Novel Approach ◽  
Latent Features ◽  
The Matrix

The concept of deep learning is used in the various fields like text, speech and vision. The proposed work deep neural network is used for recommender system. In this work pair wise objective function is used for emphasis of non-linearity and latent features. The GMF (Gaussian matrix factorization) and MLP techniques are used in this work. The proposed framework is named as NCF which is basically neural network based collaborative filtering. The NCF gives the latent features by reducing the non-linearity and generalizing the matrix. In the proposed work combination of pair-wise and point wise objective function is used and tune by using the concept of cross entropy with Adam optimization. This optimization approach optimizes the gradient descent function. The work is done on 1K and 1M movies lens dataset and it is compared with deep matrix factorization (DMF).  

Deep Neural Network Classification of I-123 Ioflupane SPECT

2020 ◽  
Author(s):  
David T. Wang ◽  
Brady Williamson ◽  
Thomas Eluvathingal ◽  
Bruce Mahoney ◽  
Jennifer Scheler
Keyword(s):  
Neural Network ◽  
Deep Neural Network ◽  
Neural Network Classification

Method of determination of the text direction on the image with the use of convolutional neural network

2020 ◽  
pp. 96-99
Author(s):  
P.L. Nikolaev
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Deep Neural Network ◽  
Binary Classification ◽  
Synthetic Data ◽  
Real Data ◽  
Method Of Determination ◽  
Classification Of Images

This article deals with method of binary classification of images with small text on them Classification is based on the fact that the text can have 2 directions – it can be positioned horizontally and read from left to right or it can be turned 180 degrees so the image must be rotated to read the sign. This type of text can be found on the covers of a variety of books, so in case of recognizing the covers, it is necessary first to determine the direction of the text before we will directly recognize it. The article suggests the development of a deep neural network for determination of the text position in the context of book covers recognizing. The results of training and testing of a convolutional neural network on synthetic data as well as the examples of the network functioning on the real data are presented.

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