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- 94%Jobber fullført
- 86%På budsjett
- 24%Gjenta ansettelsespris
Lena Image Modulation Project (MATLAB)
“Muhammad Uzair Z. is very professional. He takes the time to understand what the costumer wants and needs. He sets realistic goals and fair charges. He goes above and beyond to complete the job and satisfy the employer. He'll communicate throughout the time he is working to show the progress that is being made. He'll do the outmost to complete the job in time. Will be looking forward to working with him again in a future project.”Jason S. sist uke
“He knows his code very well. I recommend him he did a great job.”Dma K. sist uke
Project 24901130 has been deleted
“Muhammmed Uzair is dishonest freelancer. He accepted my project, and in the end, he did not deliver any piece of the work. I DONT recommend hiring him for any type of project. These words describe him: USELESS UNWORTHY DISHONEST UNKNOWLEDGEABLE”Andrew W. 1 måned siden
Project for Muhammad Uzair Z.
“he helped me with my code and improve on it, I will recommend him”Fatma A. 1 måned siden
Project 22045520 has been deleted
“This is a awesome freelancer!!! Highly recommended!!”Lashad C. 6 måneder siden
MATLAB Algorithm Develope (Image Processing)
“Always complete the project before time. I hire him two times and my experience is very positive. He can deal better with MATLAB coding.”Muhammad T. 7 måneder siden
Senior ResearcherDec 2019
Working as a researcher in the field of Biomedical Imaging, Signal Processing, Machine Learning and Deep Learning.
Research AssistantJan 2018
I am working a project which involves object tracking and localization using live video feed from camera which will be used to help visually blind people.
Research AssistantApr 2017 - Sep 2017 (5 months)
I was involved in development of a portable, remote respiratory and physical activity monitoring system.
MS Electrical Engineering (Signal Processing and Machine Learning)2016 - 2018 (2 years)
BS Telecom2012 - 2016 (4 years)
Neural Networks and Deep Learning (2018)Coursera
Automatic classification of Atrial Fibrillation from single-lead ECG signals using DCT
Automated differentiation between Normal rhythm and Atrial fibrillation using single-lead ECG signals is a challenging problem under noisy conditions and motion artifacts. In this paper we will exploit discrete cosine transform to design signal processing and machine learning algorithms for automated classification of Normal Rhythm, AF and other sinus rhythms based on single-lead ECG signals.
Preferred Freelancer Program SLA87%
US English Level 175%
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