Mohammadhossein R. Profile

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$20 USD / hour

kutaisi,

georgia

$20 USD / hour

Şu anda burada saat 9:47 ÖÖ

Ocak 9, 2021 tarihinde katıldı

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Mohammadhossein R.

@mohammadAI1995

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(0 değerlendirme)

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$20 USD / hour

kutaisi,

georgia

$20 USD / hour

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Tekrar İşe Alınma Oranı

Artificial Intelligence Researcher

My name is Mohammad Rahimzadeh and I am an Artificial Intelligence researcher and programmer. My field of research mainly focuses on computer vision and deep learning. I have published several papers on the applications of computer vision in different domains of technology and medicine. You can visit my papers at: [login to view URL] Also, you can visit some of the highlights of my works at: [login to view URL]

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Portföy

8666695

X-ray images can also be a good way of showing infection parts of the chest.

This project aimed at generating a new model for the automatic diagnosis of X-ray images. The produced model is capable of indicating the X-ray images as normal, pneumonia, and COVID-19.

Paper: A modified deep convolutional neural network for detecting COVID-19 and pneumonia from chest X-ray images based on the concatenation of Xception and ResNet50V2

Code: https://github.com/mr7495/covid19

COVID-19 detection from X-ray images

Due to the coronavirus's pandemic, AI can play a significant role in the rapid detection of infected parsons and preventing the virus from spreading and possible losses.

In this project, I have developed a robust AI-based model for diagnosing COVID-19 infected patients from CT scans. The model performs very fast with high accuracy.

Paper: A Fully Automated Deep Learning-based Network For Detecting COVID-19 from a New And Large Lung CT Scan Dataset

Code: https://github.com/mr7495/COVID-CT-Code

COVID-19 detection from CT scan images

Detecting objects in videos is a challenging problem in computer vision.

This is performed by extracting the video frames and detecting objects in each frame. In this project, we have proposed a new idea for improving object detection in video frames. Objects in the videos have one more attribute than the objects in single images, and that is their motility parameter (the point that they move and this can help in better detecting them).

We have concatenated several consecutive frames and then fed it to the network as one input. Doing this makes the network to consider the motility parameter of the objects plus other attributes.

This idea can improve object detection in videos, especially in the video with poor quality or recorded in bad conditions.

Paper: https://arxiv.org/abs/2002.04034

Code : https://github.com/mr7495/RetinaNet_Motile_objects_Detection

Motile-objects detection

Nowadays, male fertility has become a serious problem around the world. For analyzing the quality of sperms, some main parameters of sperms must be investigated. In traditional ways, the laboratory experts manually visualized the sperms with a microscope and reported the sperms' quality, which was time-consuming and not so accurate.

This project proposed a new model and algorithms to extract the sperms' fertility parameters quickly and accurately with artificial intelligence and image processing. This model is much more efficient and accurate than manual ways.

Paper: https://arxiv.org/abs/2002.04034

Code : https://github.com/mr7495/Sperm_detection_and_tracking

Sperm detection and tracking

In this project, YOLOV5 was trained for detecting cars in video frames and modified CSR-DCF was used for tracking them in frame sequences.

Cars Detection and Tracking

In the attached images, you can see some of the samples of using OpenCV; MTCNN and RetinaNet for detection human faces; eyes and body.

Face, Eyes and Body Detection

8666695

COVID-19 detection from X-ray images

COVID-19 detection from CT scan images

Motile-objects detection

Sperm detection and tracking

Cars Detection and Tracking

Face, Eyes and Body Detection

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Deneyim

Elsevier

Eyl 2020 - Şu anda

Based on my research profile, I have been selected as reviewer for several well-known journals. Some of them are: IEEE Transactions on Medical Imaging International Journal of Imaging Systems and Technology International Journal of Medical Informatics Artificial Intelligence Review Pattern Analysis and Applications Knowledge-based Systems Computers in Biology and Medicine Certificates of Reviewing are available at: https://publons.com/researcher/3639137/mohammad-rahimzadeh/

Freelancing Websites

Şub 2019 - Şu anda

As a Data Science Freelancer, I have accomplished many academic and industrial projects in the field of deep learning and computer vision.

Nitelikler

Elsevier

2020

The certificates are available at https://publons.com/researcher/3639137/mohammad-rahimzadeh/

Yayınlar

Sperm detection and tracking in phase-contrast microscopy image sequences

arXiv preprint arXiv:2002.04034

Rahimzadeh, M. and Attar, A., 2020. Sperm detection and tracking in phase-contrast microscopy image sequences using deep learning and modified csr-dcf. arXiv preprint arXiv:2002.04034. (link: https://arxiv.org/abs/2002.04034)

Detecting and Counting Pistachios based on Deep Learning

arXiv preprint arXiv:2002.04034

Rahimzadeh, M. and Attar, A., 2020. Detecting and Counting Pistachios based on Deep Learning. arXiv preprint arXiv:2005.03990. (link: https://arxiv.org/abs/2005.03990)

A fully automated deep learning-based network for detecting covid-19

medRxiv

Rahimzadeh, M., Attar, A. and Sakhaei, S.M., 2020. A Fully Automated Deep Learning-based Network For Detecting COVID-19 from a New And Large Lung CT Scan Dataset. medRxiv. (doi: https://doi.org/10.1101/2020.06.08.20121541)

A modified deep convolutional neural network for detecting COVID-19 and pneumonia

Informatics in Medicine Unlocked

Rahimzadeh, M. and Attar, A., 2020. A modified deep convolutional neural network for detecting COVID-19 and pneumonia from chest X-ray images based on the concatenation of Xception and ResNet50V2. Informatics in Medicine Unlocked, p.100360. (doi: https://doi.org/10.1016/j.imu.2020.100360)