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$30 USD / hour
Flag of PAKISTAN
rawalpindi, pakistan
$30 USD / hour
It's currently 11:37 AM here
Joined February 2, 2018
2 Recommendations

Muhammad Uzair Z.

@uzairrzahid

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4.9 (101 reviews)
6.4
6.4
$30 USD / hour
Flag of PAKISTAN
rawalpindi, pakistan
$30 USD / hour
94%
Jobs Completed
85%
On Budget
84%
On Time
23%
Repeat Hire Rate

Machine Learning and Signal Processing Expert

I am a Researcher with expertise in machine learning, Deep Learning signal processing and image processing. I have excellent programming skills. I have good grip on MATLAB, Python and C/C++. But the main thing about me is my capability to learn new things fast and work in different environment with people from different countries. Client satisfaction is my 1st priority. - 30 days error free service - Continued support after the delivery of final product - 100 % satisfaction guaranteed
Freelancer Matlab and Mathematica Engineers Pakistan

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Portfolio Items

Robust R-Peak Detection in Low-Quality Holter ECGs Using 1D
I implemented two techniques for auto-FER.

First, I retrained AlexNet, used transfer learning for classification(Transfer Learning).

Second, I used AlexNet for feature extraction and cascaded it with an SVM for classification.

I achieved 93% accuracy with AlexNet and 95% with AlexNet-SVM cascade which is comparable with the contemporary methods that give 96-98%. Data augmentation and training with larger dataset can improve the accuracy with deep learning

I used JAFFE Data Set to train my both models.
Facial Expression Recognition
The program is made with a GUI (graphical user interface) to be clear and easy to use. The images dataset which the search is made on are stored in a the folder “images”, the main GUI is coded in the two files “CBIR.fig” and”CBIR.m” but the process of features extraction is made by the code “Extract_features.m”. First the query image is loaded at this point all the previously mentioned features are extracted from the image then it is shown in the main GUI platform under title “Loaded image”. Then the extracted features are compares to the already saved and processed database where the distance between the query image and all images in the dataset is calculated. Finally the nearest ten images to the query image are shown in the GUI.

More details can be found at my Github account. 
https://github.com/MUzairZahid
Content Based Image Retrieval (MATLAB)
Train a convolutional neural network (ConvNet) for an image classification task and use the trained model for detecting cars.
CNN for Image Classification
Train a convolutional neural network (ConvNet) for an image classification task and use the trained model for detecting cars.
CNN for Image Classification
Train a convolutional neural network (ConvNet) for an image classification task and use the trained model for detecting cars.
CNN for Image Classification
In this project, I implemented an automated algorithm to classify, from a single short ECG lead recording , whether the recording shows normal sinus rhythm, atrial fibrillation (AF), an alternative rhythm, or is too noisy to be classified.
Heart Arrhythmia Classification using ECG Signal
In this project, I implemented an automated algorithm to classify, from a single short ECG lead recording , whether the recording shows normal sinus rhythm, atrial fibrillation (AF), an alternative rhythm, or is too noisy to be classified.
Heart Arrhythmia Classification using ECG Signal
In this project, I implemented an automated algorithm to classify, from a single short ECG lead recording , whether the recording shows normal sinus rhythm, atrial fibrillation (AF), an alternative rhythm, or is too noisy to be classified.
Heart Arrhythmia Classification using ECG Signal
In this project, I implemented an automated algorithm to classify, from a single short ECG lead recording , whether the recording shows normal sinus rhythm, atrial fibrillation (AF), an alternative rhythm, or is too noisy to be classified.
Heart Arrhythmia Classification using ECG Signal
In this project, I implemented an automated algorithm to classify, from a single short ECG lead recording , whether the recording shows normal sinus rhythm, atrial fibrillation (AF), an alternative rhythm, or is too noisy to be classified.
Heart Arrhythmia Classification using ECG Signal

Reviews

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Showing 1 - 5 out of 50+ reviews
Filter reviews by: 5.0
$150.00 AUD
Yet more repeat business from me and I'll be going back for more!
Matlab and Mathematica Algorithm Electrical Engineering Machine Learning (ML)
+1 more
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Flag of Jacob A. @mintgreenstrat
3 months ago
5.0
$75.00 AUD
Hiring Uzair for the second time and he once again delivered quickly and accurately. I will be hiring again.
Matlab and Mathematica Algorithm Electrical Engineering Machine Learning (ML)
+1 more
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Flag of Jacob A. @mintgreenstrat
6 months ago
5.0
$40.00 USD
Good work was done by him
Python Image Processing
J
Flag of Jai P. @jaypurugu7
6 months ago
5.0
$55.00 USD
Freelancer is very precise and did an excellent job. He submitted ahead of time which is great.
Engineering Electronics Matlab and Mathematica Electrical Engineering
M
Flag of Mohammed K. @Mwmkhalil
6 months ago
5.0
₹1,000.00 INR
He is very honest with what he can do and what he cannot do, he keeps you updated with his progress and does quality work. Hire him if you want an honest and skillful freelancer.
Python Software Architecture Machine Learning (ML)
User Avatar
Flag of Marco Antonio M. @sonianaya
6 months ago

Experience

Senior Researcher

Qatar University
Dec 2019 - Present
Working as a researcher in the field of Biomedical Imaging, Signal Processing, Machine Learning and Deep Learning.

Research Assistant

CE FAR LAB
Jan 2018 - Present
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 Assistant

SIGMA LABS NUST (Research Lab for Signal Processing And Machine Learning)
Apr 2017 - Sep 2017 (5 months, 1 day)
I was involved in development of a portable, remote respiratory and physical activity monitoring system.

Education

MS Electrical Engineering (Signal Processing and Machine Learning)

National University of Science and Technology, Pakistan 2016 - 2018
(2 years)

BS Telecom

University of Engineering and Technology, Taxila, Pakistan 2012 - 2016
(4 years)

Qualifications

Neural Networks and Deep Learning

Coursera
2018

Publications

Robust Peak Detection for Holter ECGs by Self-Organized Operational Neural Networks

IEEE Transactions on Neural Networks and Learning Systems
In this study, to further boost the peak detection performance along with an elegant computational efficiency, we propose 1D Self-Organized Operational Neural Networks (Self-ONNs) with generative neurons. The experimental results over the China Physiological Signal Challenge-2020 (CPSC) dataset show that the proposed 1D Self-ONNs can significantly surpass the state-of-the-art deep CNN with less computational complexity.

Robust R-Peak Detection in Low-Quality Holter ECGs using 1D Convolutional Neural Network

IEEE Transactions on Biomedical Engineering
In this study, a novel implementation of the 1D Convolutional Neural Network (CNN) is used integrated with a verification model. Experimental results demonstrate that the proposed systematic approach achieves 99.30% F1-score, 99.69% recall, and 98.91% precision in CPSC-DB, which is the best R-peak detection performance ever achieved. Results also demonstrate similar or better performance than most competing algorithms on MIT-DB with 99.83% F1-score, 99.85% recall, and 99.82% precision.

Automatic classification of Atrial Fibrillation from single-lead ECG signals using DCT

Submitted to Physiological Measurement special issue.
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.

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Top Skills

Matlab and Mathematica 71 Algorithm 52 Machine Learning (ML) 50 Electrical Engineering 47 Data Science 33

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