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xiangpeng2023

0.0 (0 Reviews)
China

About Candidate

Two years's experience in computer vision in the lastest job, using python, pytorch, c++. Defect inspection with deep learning methods like classification, detection and segmentation with yolo, achieved very good result. Anomaly inspection with RegAD method, modified network and successfully applied in real application.One year's experience in NLP and also several years' experience in web development, c# development and recommendation system. 

Skills

python
90%
c++
90%
pytorch
90%

Work & Experience

s
2023-03 - Until Now software
Full-time
Easyview

China Hubei Wuhan

<ul> <li>End defects of cigarettes detection, such as hollow ends and loose ends. Using VS, C++, OpenCV, and QT, achieved good result.</li> <li>Seal defects of cigarettes end detection. Using C++, OpenCV, and YOLOv8, achieved good result.</li> <li>Phase and gap defects of various tobacco composite rods detection. Using C++ and OpenCV, achieved good result.</li> <li>Surface defects detection of composite rods with materials, such as material clamping, damage, phase, and insufficient material. Using C++ and Yolov8, achieved good result.</li> <li>Detection of defects such as holes, uneven arrangement, and protrusion of plate filled with composite rods. Using C++, OpenCV, and deep learning classification algorithms.</li> <li>Detection of defects such as aluminum foil pitting, scratches, and missed coating, with deep learning classification algorithms, achieved good result.</li> <li>Detection of printed text defects and printed paper surface defects, with anomaly detection deep learning algorithms. Modified the RegAD algorithm to meet the application need.</li> <li>Design general dection algorithm for rod inspection.</li> </ul>

Education

m
2006-09 - 2008-07 Master
Huazhong University of Science and Technology

China Hubei Wuhan

Languages

English
80%
Chinese
100%

Certifications

Awards

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