softgel detection
Training segmentation model to get the region of the softgel on the image (real time inspection)
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I am a Computer Vision Engineer with extensive experience in machine learning, image processing, and AI-driven defect detection for industrial and pharmaceutical applications. My background includes developing real-time computer vision systems, building and cleaning datasets, and applying deep learning models such as U-Net for semantic segmentation of satellite imagery. I have hands-on expertise with data annotation, dataset preparation, and training data management using tools like Python, OpenCV, TensorFlow, and PyTorch. My work often involves collaborating on R&D projects, optimizing data workflows, and ensuring high-quality labeled data for robust AI model development. I am passionate about leveraging my technical skills to improve data quality and support innovative AI solutions across various domains.
Training segmentation model to get the region of the softgel on the image (real time inspection)
Training anomaly detection model for coin inspection
Master of Science, Computer Vision and Signal Processing
Master of Science, Industrial Engineering – Information Technology and Automation
Vision Engineer
Software Engineer