#character recognition

[algopop]

[chineselearning777]

Come and learn Chinese words!!(1)

[friendschinese]

Come and learn Chinese words!!(1)

[whisperingchinese]

Come and learn Chinese words!!(1)

[ijtsrd]

Automated License Plate detection and Speed estimation of Vehicle Using Machine Learning Haar Classifier Algorithm

by P. Devi Mahalakshmi | Dr. M. Babu "Automated License Plate detection and Speed estimation of Vehicle Using Machine Learning - Haar Classifier Algorithm"

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-6 , October 2020,

URL: https://www.ijtsrd.com/papers/ijtsrd33395.pdf

Paper Url: https://www.ijtsrd.com/engineering/computer-engineering/33395/automated-license-plate-detection-and-speed-estimation-of-vehicle-using-machine-learning--haar-classifier-algorithm/p-devi-mahalakshmi

peerreviewedjournals, reviewpapers, callforpaperhealthscience

A well ordered traffic management system is required in all types of roads, such as off roads, highways, etc. There has been several laws and speed controlled measures are taken in all places with different perspectives. Also Speed limit may vary from road to road. So there are number of methods has been proposed using computer Vision and machine learning algorithms for object tracking. Here vehicles are recognized and detected from the videos that taken using surveillance camera. The aim is to identification of the vehicles and tracking using Haar Classifier, then determine the speed of the vehicle and Finally Detecting the License plate of the vehicle. Detecting the License plate and vehicle speed using machine learning is tough but beneficial task. For the past few years Convolution Neural Network CNN has been widely used in computer vision for vehicle detection and identification. Dlibs are used to track the multiple objects at the same time. 

[attorneyandlawyer]

NEURAL NETWORKS FOR UNICODE OPTICAL CHARACTER RECOGNITION

NEURAL NETWORKS FOR UNICODE OPTICAL CHARACTER RECOGNITION

NEURAL NETWORKS FOR UNICODE OPTICAL CHARACTER RECOGNITION

TABLE OF CONTENT Title page- – – – – – – – – i Approval page – – – – – – – -ii Dedication – – – – – – – – -iii Acknowledgement – – – – – – – -iv Abstract – – – – – – – – – -v Table of content – – – – – – – -vi

CHAPTER ONE INTRODUCTION – – – – – – – -1 1.0 Background of the study – – – – -1 1.1 Statement of the problem – – – – -5 1.2 Purpose…

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[ijtsrd]

Reconstructing the Path of the Object based on Time and Date OCR in Surveillance System

by Pyae Phyo Thu | Mie Mie Tin | Ei Phyu Win | Cho Thet Mon ""Reconstructing the Path of the Object based on Time and Date OCR in Surveillance System""

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019,

URL: https://www.ijtsrd.com/papers/ijtsrd27981.pdf  

Paper URL: https://www.ijtsrd.com/home-science/education/27981/reconstructing-the-path-of-the-object-based-on-time-and-date-ocr-in-surveillance-system/pyae-phyo-thu

pharmacy journal, open access journal of engineering, research publication

The inclusion of time based queries in video indexing application is enables by the recognition of time and date stamps in CCTV video. In this paper, we propose the system for reconstructing the path of the object in surveillance cameras based on time and date optical character recognition system. Since there is no boundary in region for time and date, Discrete Cosine Transform DCT method is applied in order to locate the region area. After the region for time and date is located, it is segmented and then features for the symbols of the time and date are extracted. Back propagation neural network is used for recognition of the features and then stores the result in the database. By using the resulted database, the system reconstructs the path for the object based on time. The proposed system will be implemented in MATLAB. 

[ourwitching]

We’ve all come to terms with a neural network doing jobs such as handwriting recognition. The...