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KNN MNIST with HOG feature
“Delivered on time and [login to view URL] you”Shadman M. ontem
Signals and systems Analysis
“He tried hard to complete the project but it was not completed and I missed my deadline.”Abdul W. 3 dias atrás
“the guy did well, i would lke to hire him again!”Guoxiao T. semana passada
MATLAB Program - emotion recognition
“He is a clever person, very smart and a good programmer. The project was delivered before the time limit and the expectations were reached. Also he is very patient and can explain everything so you can understand his work. I totally recommend Muhammad and i am going to contact him for future projects :) Good job man! Keep up the good work.”Cosmin Stefan M. semana passada
Project for Muhammad Uzair Z. -- 2
“He was good with his work. Would love to work with him again.”Abhi Nishanth R. há 3 semanas
Project for Muhammad Uzair Z.
“I am very happy working with him the work was done in a professional way I asked for a lot of modification and he did it .... the work was delivered on time I will definitely hire him again recommend him”Asmaa A. há 4 semanas
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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