132650027695
Seller assumes all responsibility for this listing.
Shine x 36cm 9cm Effect Gold Toilet Accessory Bathroom Rose Brush Plastic 6ZFrq6X
Shine 36cm Gold x Accessory 9cm Effect Rose Brush Toilet Plastic Bathroom
9cm Bathroom Brush Rose Shine Gold Effect Accessory Plastic 36cm x Toilet
Advertisement

Abstract: Optical Character Recognition is the process of converting an input text image into a machine encoded format. Different methods are used in OCR for different languages. T... View more
Abstract:
Optical Character Recognition is the process of converting an input text image into a machine encoded format. Different methods are used in OCR for different languages. The main steps of optical character recognition are pre-processing, segmentation and recognition. Recognizing handwritten text is harder than recognizing printed text. Convolutional Neural Network has shown remarkable improvement in recognizing characters of other languages. But CNNs have not been implemented for Malayalam handwritten characters yet. The proposed system uses Convolutional neural network to extract features. This is method different from the conventional method that requires handcrafted features that needs to be used for finding features in the text. We have tested the network against a newly constructed dataset of six Malayalam characters. This is method different from the conventional method that requires handcrafted features that needs to be used for finding features in the text.
Date of Conference: 10-11 March 2017
Date Added to IEEE Xplore: 17 July 2017
ISBN Information:
INSPEC Accession Number: 17042251
Publisher: IEEE
Conference Location: Coimbatore, India
Advertisement

I. Introduction

Deep learning Techniques has achieved top class performance in pattern recognition tasks. These include image recognition [1], [2], human face recognition [3], human pose estimation [4] and character recognition [5], [6]. These deep learning techniques have proved to outperform traditional methods for pattern recognition. Deep learning enables automation of feature extraction task. Traditional methods involve feature engineering which is to be done manually. This task of crafting features is time consuming and not very efficient. The features ultimately determine the effectiveness of the system. Deep learning methods outshine traditional methods by automatic feature extraction.

Air AT157A Off Cut Point Tool 21000 3 Blue RPM Pneumatic xSq4nx
Advertisement
Advertisement
ZRX1200R Vehicle Series Bullet Basic Type KAWASAKI Exclusive Blinker Set POSH nFAZH7zH