Ebrahim Parcham Email & Phone Number

Tehran Province, Iran

Tehran, Iran

Face Detection in Videos for Fraud Analysis: I have developed sophisticated algorithms capable of identifying fake faces in videos. This advancement is crucial in combating deepfake technologies and ensuring the authenticity of digital content in media and communications. Fraud Detection in Banking Checks and OCR Technology: My work has extended to the financial sector, where I designed systems for detecting fraud in bank checks alongside implementing OCR (Optical Character Recognition) technology. This dual approach not only enhances security measures but also streamlines banking operations by automating the verification of check authenticity and details. Generalized OCR for Diverse Images: Recognizing the need for broad-spectrum OCR solutions, I have created a versatile OCR system applicable to a wide range of images. This technology enables the extraction and digital conversion of text from any image, facilitating data processing and accessibility across various industries. Passport and ID Fraud Detection: In response to the increasing sophistication of document forgery, I have focused on developing AI-based techniques for detecting passport and ID fraud. This work is vital for enhancing security measures in immigration, law enforcement, and identity verification processes.

Tehran Province, Iran

As a judge, I have been responsible for evaluating various knowledge-based projects submitted by Iranian companies in the field of artificial intelligence. This includes assessing the technical aspects of the projects, their practicality, and their potential impact on the industry. The goal is to identify the most innovative and promising projects that can contribute to the growth and advancement of the field.

Tehran, Iran

1. Algorithm design for object segmentation in images with deep learning techniques• Achieved processing speed of 25 frames per second• Conducted literature review and implemented and compared latest research articles2. Mobile bank application design using deep learning algorithms• Implemented in Python and TensorFlow, and converted to Java for Android• Achieved processing speed of 150 milliseconds for identifying bank card number, expiration date, and CVV2 number3. System for accurately recognizing and confirming customer signatures in banking systems• Achieved high accuracy rate of 96%• Submitted work as article to Q1 journal• Conducted literature review, implemented existing articles using TensorFlow, and compared with proposed method4. Intelligent automatic system for reading power meters using deep learning techniques• Developed fake database for all types of power meters in Iran with all possible effects automatically• Achieved accuracy rate of 93% for medium to poor image quality and 98% for medium to good images5. System for recognizing and reading national ID cards, barcodes, and national ID numbers using TensorFlow• Used in Pepper Robot of Khatam University• Achieved speed of 30 frames per second on ordinary Android phones6. Conducted research on predicting market trends using deep learning and data mining techniques on stock market data7. Designed architecture for face recognition system using deep learning and image processing techniques

Tehran

• Designing and coding for object detection and distance estimation based on deep learning and image processing.• Designing and coding a complete system for license plate recognition (LPR), including recognition of vehicle and license plate locations, reading of the license plate, and recording of vehicle speed.• Building an automatic system to generate a database for the license plate reader system and object detection.• Designing a precision control system using deep learning for the Intelligent Transportation System (ITS) for Barsam road and urban traffic control systems.

Iran

• Designed and tested a breast cancer detection system with mammography images at ALZAHAR Hospital• Under the supervision of Dr. Fatemeh Ghatre Samani• Achieved an accuracy rate of 93% and tested in Tabriz• Designed to be comparable to Siemens's CAT system• Conducted research on EEG signals for diagnosing epilepsy• Conducted the research on 120 epileptic patients at Razi Hospital in Tabriz.

Shiraz

A system for sound classification has been designed and programmed to achieve accurate sound classification in crowded environments, with an impressive accuracy rate of 96%.

Doctor Of Philosophy - Phd, Artificial Intelligence, 3.93 Gpa

Master'S Degree, Artificial Intelligent, 3.6 Gpa

Bachelor Of Computer, Computer Software Engineering, 3.7