Joe Afshany

I got my masters degree from University of Guilan. I worked with a lot of programming languages, such as Basic, Assembly, FoxPro, Visual FoxPro, Pascal, C, C++, C#, PHP, and etc.

Now I work in These fields:

  • Web Developing  using HTML, CSS, JavaScript, MySQL, AJAX technology and PHP.
  • Image Processing and Machine Vision fields. Specially License plate Detection and Vehicle Speed Measurement using C++/C#, OpenCV/EmguCV.
  • Parallel programming on GPU using C++ and CUDA Tookit.
  • Mobile Game Developing using C# and Unity 3D.

What I Do

Web Developing

Web Developing

Since 2014 I have experience as PHP Developer in analysis, design, development, and management. ( Skills : PHP, Linux Server, JavaScript, JQuery, AJAX, MySQL, HTML5, CSS3 )

Wordpress

Wordpress

Since 2011 I am using WordPress for create some websites by customizing its template and codes.

Mobile Game Developing

Mobile Game Developing

Since 2019 I started Game Developing for Mobile devices. Now I am working on my first Mobile game. ( Skills : Unity3D, C# ).

Machine Vision and Image Processing

Machine Vision and Image Processing

Sine 2017 I am working on Machine vision and Image Processing. I work in fields such as License Plate Detection, and Vehicle Speed Measurement using Image Processing. (Skills : C++, OpenCV)

Parallel Programming

Parallel Programming

Since 2017 I am using Parallel Programming on GPU for increase computational speed of Image Processing. ( Skills : C++, CUDA Toolkit).

Resume

26 Years of Experience

Education

2018
University of Guilan

Masters, Computer Software Engineering

University of Guilan Web Page

2015
Azad University of Bandar Anzali

Bachelor, Computer Software Engineering

Azad University of Bandar Anzali Web Page

1999
Shahid Rajaee University of Lahijan

Associate, Computer Software Engineering

Shahid Rajaee University of Lahijan Web Page

Experience

2019 - Current

Mobile Game Developing

Since 2019 I am working on Mobile Game Developing using Unity3D and C#.

2017 - Current

Machine Vision and Image Processing

Since 2017 I am working in Machine Vision and Image Processing fields. My main branch in this field is License Plate Detection and Vehicle Speed Measurement.

2017 - Current

GPU Programming

Since 2017 I am working on GPU programming to speed up execution of commands in parallel.

2014 - Current

Web Developing

Since 2014 I am working as a web developer.

2001 - 2009
Arvin

As a programmer

I Worked in Arvin Co. as a programmer for create softwares such as Salary, Warehouse Management, Accounting, Hospital Schedule, and etc.

1994

Programming Start

I Started programming since 1994. I started programming in some languages that were famous at that time, such as GW Basic, Basic, Pascal, Foxpro, Turbo C, and etc.

Design Skills

Web Design

95%

Print Design

65%

Logo Design

80%

Graphic Design

90%

Coding Skills

C++

90%

JavaScript

85%

PHP

70%

HTML / CSS

100%

GPU Programming

70%

Unity 3D / C#

80%

Published

My Publishes

Parallel Implementation of a Video-based Vehicle Speed Measurement System for Municipal Roadways (2019)

Nowadays, Intelligent Transportation Systems (ITS) are known as powerful solutions for handling traffic-related issues. ITS are used in various applications such as traffic signal control, vehicle counting, and automatic license plate detection. In the special case, video cameras are applied in ITS which can provide useful information after processing their outputs, known as Video-based Intelligent Transportation Systems (VITS). Among various applications of V-ITS, automatic vehicle speed measurement is a fast-growing field due to its numerous benefits. In this regard, visual appearancebased methods are common types of video-based speed measurement approaches which suffer from a computationally intensive performance. These methods repeatedly search for special visual features of vehicles, like the license plate, in consecutive frames. In this paper, a parallelized version of an appearance-based speed measurement method is presented which is real-time and requires lower computational costs. To acquire this, datalevel parallelism was applied on three computationally intensive modules of the method with low dependencies using NVidia’s CUDA platform. The parallelization process was performed by the distribution of the method’s constituent modules on multiple processing elements, which resulted in better throughputs and massively parallelism. Experimental results have shown that the CUDA-enabled implementation runs about 1.81 times faster than the main sequential approach to calculate each vehicle’s speed. In addition, the parallelized kernels of the mentioned modules provide 21.28, 408.71 and 188.87 speed-up in singularly execution. The reason for performing these experiments was to clarify the vital role of computational cost in developing video-based speed measurement systems for real-time applications.

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Works

Some of My Works
image

Vehicle Speed Measurement

Method

Using Video Frames Processing

Programming

Programming

C++ (OpenCv/Cuda Toolkit)

More Details


image

Specialized network of technology companies

Platform

Platform

Web Programming

Programming

Programming

PHP, HTML, CSS, JavaScript, AJAX Technology, MySQL Database

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Contact

Get in Touch

+98-911-132-2523

Rasht/Gilan/Iran

joe.afshany@gmail.com

Freelance Available

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