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Shakhzodbek-Yuldoshov
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- Computer Vision Intern
- Bachelors degree in Computer Engineering
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Shakhzodbek Yuldoshov Computer Vision Engineer Tashkent 100142 shahzodbek.yuldoshov@gmail.com 998901391331 Sponsorship required to work in the UK Work Experience Computer Vision Engineer Octobot - Seoul March 2022 to Present Completing 3 little and 1 bigger than others project from beginning till the end. Completed project names: Traffic sign recognition and find location, Car Dashboard analytics, Anonymization, Drowsiness detection. Description about every project Traffic sign recognition and find location - in this project 145 types of Korean traffic signs should be detected and every text written inside it should be recognized, should calculate its location using gps data and deploy to edge devices. Car Dashboard Analytics - ADAS, LKAS, speed, time, location and write it into csv file. Anonymization - blur faces of people and license plate (personal informations) for various purposes. Drowsiness detection - collect data about driver whether driver is yawning, eyes are closed, which side driver is looking at. The most complicated project was traffic sign recognition and find location. The most complicated part was deploying ready project into edge device. We tried several devices as Jetson nano, raspberry pi 4, jetson AGX using cameras with VPU chip like OAK-D, OAK-D CM4, ZED2. And we used Jetson AGX and Zed2 camera. You may have question like why you chose those devices: The answer would be We tried raspberry pi and Jetson nano with OAK-D camera. OAK-D's computational power is not enough for model that we trained. To deploy on that AI camera we should optimize the model and model accuracy may decrease after optimization. Tried to use OAK-D as stereo camera not use its VPU for model inference but there is no information to use it as stereo camera. So we decided to use ZED2 camera to use as Stereo camera and now we need to find device where computation power would be enough for model inference. So we decided to use Jetson Xavier AGX. Computer Vision Intern ITMED Uzbekistan - Tashkent July 2021 to February 2022 Convert Dicom image type to png and helping doctors to label breast cancer dicom images. Using yolov5 for breast cancer detection in BIRADS system. Masked-RCNN for breast cancer segmentation Resnet-50 to classify whether given image is malignant or benign for COVID-19 classification. Tried to connect Our model to PACS system but failed. Computer Vision Intern TASS Vision - Tashkent April 2021 to July 2021 Gathering and preprocessing dataset for the project named Visitor analytics. This helped to increase model accuracy (100%) in real life tests. Learning how camera works and testing cameras for spoof attacks for face recognition cameras. Found several conditions where face recognition is not working. Education Bachelor's degree in Computer Engineering Tashkent University of Information Technologies named after Muhammad al-Khwarizmi - 108 Amir Temur avenue Tashkent, 100084 September 2022 to Present Bachelor's degree in Computer Engineering Inha University in Tashkent - 9 Ziyolilar St, Tashkent September 2020 to May 2021 College Degree in Taxation Tashkent Tax College - 3 Little Ring Road, Tashkent 100173 September 2016 to May 2020 Skills • Linux • AI • PyTorch • Deep learning • Python • optical character recognition • YOLO Languages • Uzbek - Fluent • English - Intermediate • Russian - Intermediate Links https://github.com/ShakhzodbekYuldoshov https://www.linkedin.com/in/shakhzodbek-yuldoshov-4ba477203/ Download 63.39 Kb. Do'stlaringiz bilan baham: 
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