Highly skilled and innovative Computer Vision Engineer with a strong background in developing cutting-edge solutions for image and video analytics. Experienced in leveraging deep learning, machine learning, and computer vision algorithms to tackle complex problems in various industries. Passionate about advancing the field of computer vision and driving impactful applications in areas such as medical imaging, and augmented reality.
Machine Learning Frameworks:
Pytorch | Tensorflow | ONNX | TensorflowLite | OpenCV | PCL | Open3D | Tensorrt | PyCoral | OpenVino
Computer Vision Tasks:
image classification | object detection | image segmentation | synthetic data genertion
Progrmming Languages:
Python | C++ | C (micro-controllers)
Web Developement:
Tornado | Flask | FastAPI
User Interface:
Qt | Streamlit | Gradio | HTML
Opensource contributions:
CVAT | YoloV5 | YoloV7 | YoloV8 | Supervision | Ultimate Labelling | EyeQ | EyeQ-Foundation | CVAT Plugins | Label-studio ML Backend | YoloExplorer
Edge Devices:
Upboards | EdgeTPU | Jetson | Raspberry Pi | Luxonis OAK Devices | Myriad X
Others:
DevOps | MLOps | Git | DVC