• Designed a self-annotation system for annotating object detection data (Raw data)
• Provided technical support to clients and collaborated with cross-functional teams to resolve technical issues
• Actively participate and contribute to the internal data science project initiatives
• Improved model inference speed by 20% in projects: Automatic License Plate Recognition and Face Recognition, utilizing Nvidia CUDA and CUDNN.
• Designed and custom-trained Object detection (YOLOv4)/OCR frameworks, including CRNN and Tesseract OCR, optimizing deep-learning solutions.
• Assembled 100k+ data points for diverse deep-learning model training, ensuring robust datasets.
• Conducted precise data annotation using Computer Vision Annotation Tool (CVAT) for custom object detection.
• Proficient in various IDEs like Google Colab, Jupiter Lab, PyCharm, and VS Code for seamless development.
• Collaborated with cross-functional teams, addressing 100+ critical technical issues and enhancing project efficiency.