Automated Mineral Identification Software Development

I'm looking for a Computer Science Specialist with strong expertise in AI, ML, and digital image processing to create a Windows-based software application for automated mineral identification. The application will utilize photomicrographs of thin sections and should leverage AI and advanced imaging technologies to accurately and efficiently identify and classify minerals.

Key Project Components:
- Development of a Windows-compatible application.
- Implementation of supervised learning techniques for mineral classification.
- Use of TensorFlow, Scikit Learn and OpenCV for AI implementation.

Ideal Skills and Experience:
Develop an AI-based image processing framework for mineral identification in thin sections.

Design and implement convolutional neural networks (CNNs) for image classification tasks.

Preprocess and analyze thin-section images under plane-polarized and cross-polarized light.

Train, validate, and test machine learning models for high accuracy and reproducibility.

Optimize software tools using Python and relevant libraries such as TensorFlow, OpenCV, and Scikit-learn.

Evaluate and compare model performance with traditional mineral identification methods.

Collaborate with geologists to ensure the software meets mineralogical analysis standards.