scholarly journals A Neural Network Approach for Birds of a Feather Solvability Prediction

2019 ◽  
Vol 33 ◽  
pp. 9706-9712
Author(s):  
Benjamin Sang ◽  
Sejong Yoon
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Deep Neural Network ◽  
Machine Learning Method ◽  
Card Game ◽  
Learning Method ◽  
Solution Path ◽  
Network Approach ◽  
Neural Network Approach ◽  
Search Spaces

Birds of a Feather is a single player, perfect information card game. The game can have multiple board sizes with larger boards introducing larger search spaces that grow exponentially. In this paper, we investigate the solvability of the game, aiming at building a machine learning method to automatically classify whether a given board state has a solution path or not. We propose a method based on image-based features of the board state and deep neural network. Experimental results show that the proposed method can make reasonable predictions of the solvability of a game at an arbitrary stage of the game.

An Useful Review on Optical Character Recognition for Smart Era Generation

2021 ◽  
pp. 1-41
Author(s):  
Abhishek Das ◽  
Mihir Narayan Mohanty
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Image Processing ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Deep Neural Network ◽  
Machine Learning Method ◽  
Learning Method ◽  
Result Section ◽  
Optical Character

In this chapter, the authors have reviewed on optical character recognition. The study belongs to both typed characters and handwritten character recognition. Online and offline character recognition are two modes of data acquisition in the field of OCR and are also studied. As deep learning is the emerging machine learning method in the field of image processing, the authors have described the method and its application of earlier works. From the study of the recurrent neural network (RNN), a special class of deep neural network is proposed for the recognition purpose. Further, convolutional neural network (CNN) is combined with RNN to check its performance. For this piece of work, Odia numerals and characters are taken as input and well recognized. The efficacy of the proposed method is explained in the result section.

scholarly journals Leaf Features Extraction for Plant Classification using CNN

2021 ◽  
pp. 148-154
Author(s):  
Mr. P. Siva Prasad ◽  
Dr. A. Senthilrajan
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Neural Networks ◽  
Deep Learning ◽  
Deep Neural Network ◽  
Research Area ◽  
Network Approach ◽  
Neural Network Approach ◽  
Active Research ◽  
Active Research Area

Deep learning is now an active research area. Deep learning has done a success in computer vision and image recognition. It is a subset of the Machine Learning. In Deep learning, Convolutional Neural Network (CNN) is popular deep neural network approach. In this paper, we have addressed that how to extract useful leaf features automatically from the leaf dataset through Convolutional Neural Networks (CNN) using Deep Learning. In this paper, we have shown that the accuracy obtained by CNN approach is efficient when compared to accuracy obtained by the traditional neural network.

scholarly journals An optimized Deep Neural Network Approach for Vehicular Traffic Noise Trend Modelling

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Ahmed Abdulkareem Ahmed ◽  
Biswajeet Pradhan ◽  
Subrata Chakraborty ◽  
Abdullah Alamri ◽  
Chang-Wook Lee
Keyword(s):  
Neural Network ◽  
Deep Neural Network ◽  
Traffic Noise ◽  
Vehicular Traffic ◽  
Network Approach ◽  
Neural Network Approach

Validating the impact of accounting disclosures on stock market: A deep neural network approach

2021 ◽  
Vol 170 ◽  
pp. 120903
Author(s):  
Prajwal Eachempati ◽  
Praveen Ranjan Srivastava ◽  
Ajay Kumar ◽  
Kim Hua Tan ◽  
Shivam Gupta
Keyword(s):  
Neural Network ◽  
Stock Market ◽  
Deep Neural Network ◽  
Network Approach ◽  
Neural Network Approach ◽  
Accounting Disclosures ◽  
The Impact

Determination of thermodynamic state variables of liquids from its microscopic structure using an artificial neural network

Soft Matter ◽  
2020 ◽  
Author(s):  
Ulices Que-Salinas ◽  
Pedro Ezequiel Ramirez-Gonzalez ◽  
Alexis Torres-Carbajal
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Artificial Neural Network ◽  
Distribution Function ◽  
Microscopic Structure ◽  
Machine Learning Method ◽  
Learning Method ◽  
State Variables ◽  
Thermodynamic State

In this work we implement a machine learning method to predict the thermodynamic state of a liquid using only its microscopic structure provided by the radial distribution function (RDF). The...

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