[PDF] Top 20 Text Recognition using Convolutional Neural Network: A Review

Text Recognition using Convolutional Neural Network: A Review

... The proposed structured of the survey is a three layer architecture. First is the input layer which receives input from the segmented character images of standard size. Second layer is a hidden layer, this layer is use ... See full document

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License Plate Character Recognition using Riesz Fractional and Convolutional Neural Network

... plate recognition system is mostly used for identification of ...plate recognition is low quality of images which affected via severe illumination ...of text recognition. The text in ... See full document

5

Text-Attentional Convolutional Neural Network for Scene Text Detection

... scene text localization and recognition method is ...estimated using novel features ...improved using more computationally expensive ...Finally, text is recognized in an OCR stage ... See full document

15

The Understanding of Convolutional Neuron Network Family

... computers. Convolutional Neural Network (CNN) is one of the most popular algorithms in the field of Deep ...voice, text recognition and other aspects of the ...theory, ... See full document

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Khmer handwritten text recognition with Convolution Neural Networks

... symbols recognition using Convolutional Neural Networks ...a recognition system for digitizing large corpora of Khmer handwritten ...offline recognition of root radicals where ... See full document

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Human Face Recognition in Video using Convolutional Neural Network (CNN)

... scale video sequence [3]. VFR faces challenges like variation in pose and occlusion and its main aim is to recognize the face from video-based face patches. The dataset is Yaleface database that are taken frame by frame ... See full document

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Automatic diagnosis of imbalanced ophthalmic images using a cost-sensitive deep convolutional neural network

... Exploring the effectiveness of the combinations of cost‑sensitive and data‑level methods Since the data-level methods and cost-sensitive are two powerful techniques for address- ing the imbalanced dataset from different ... See full document

20

Handwritten Bangla Character Recognition using Inception Convolutional Neural Network

... of convolutional layer. On its own, a convolutional layer is not rotation invariant that means the model is not good at classifying rotating testing image ... See full document

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Vehicle Recognition Based On Convolutional Neural Network

... of network, training of 5 times is more ...of network is small.The training of 5 times of the network to get the feature classifier training time and recognition time is the ...the ... See full document

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A Convolutional Neural Network for Handwritten Digit Recognition

... a neural network with multiple layers, trained with a version of the back-propagation algorithm and it is designed to recognize visual patterns directly from pixel images with minimal ...Many network ... See full document

9

3D Convolutional Neural Network for Object Recognition

... et al. [19] developed first CNN architecture for volume based data, namely 3DShapeNets. 3DShapeNets used a Deep Belief Network to represent geometric 3D shapes as a probability distribu- tion of binary variables ... See full document

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Integrated Animal Recognition and Detection Using Deep Convolutional Neural Network

... The above figure shows the Color Segmented Image.The most widely used color space is the color space, where a color point in the space is characterized by three color components of the corresponding pixel which are red ... See full document

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Design And Development Of A License Plate Recognition System Using Convolutional Neural Network

... character recognition process is the most challenging ...the recognition of the characters is highly dependent on the type of algorithms applied in the first four major ...character recognition ... See full document

24

Survey on Image Text Detection and Recognition of Natural Scene Images

... a convolutional neural network based scene text detection algorithm along with a new text region extractor wasproposed to improve the independency and completeness of the extract ... See full document

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Candle Stick Pattern Recognition Using Convolutional Neural Network (ResNet)

... Quantmod is a special package in R that is dedicated to Financial analysis of the stock market. There are lot of useful functions in this package such as getting the end-of-day of the stocks listed is almost every ... See full document

7

Fruit Recognition Using Deep Convolutional Neural Network With Color Feature

... Convolution Neural Network is one kind of artificial network, which is helpful in image identification, classification, extraction and processing the ...Artificial Neural Networks uses deep ... See full document

5

Iris Recognition using Convolutional Neural Network Design

... for recognition rate with state of art approaches. The recognition rate obtained is summarized in table ...varying recognition rates for same data ...the recognition rates are nearly equal on ... See full document

7

Recognition of Brahmi words by Using Deep Convolutional Neural Network

... environment using a momentum value of ...of convolutional cores gradually to reach the optimum state of the network because of the overfitting ...word recognition. Efficiency graphs ... See full document

9

Developing A Face Recognition System Using Convolutional Neural Network

... Face recognition is a biometric method that uses features of face to identify ...face recognition is hard to handle due to pose invariant, illumination invariant and many ... See full document

24

A NOVEL TWO DIMENSIONAL SPECTRAL/SPATIAL HYBRID CODE FOR OPTICAL CODE DIVISION MULTIPLE ACCESS SYSTEM

... An ear recognition method is proposed by Revaud et al. [18], which uses the Scale-Invariant Features Transform (SIFT) method to detect features and create descriptors for them. These features are extracted for the ... See full document

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