AI Photography Assistant

In the module “Professional Product Development Case Study”, I coordinate the development of an intelligent photography assistant. The six-person team pursues a strictly explainable approach.

The system combines modern computer vision with transparent decision models. Unlike classic black-box systems, the focus is on traceability, measurability and auditable recommendations.

Decisions are accompanied by uncertainty indicators and human-readable explanations. The architecture is modular, API-driven and testable.

The XAI focus includes explainable decision trees, visual relevance maps and confidence analyses to maximise trust and interpretability.

Technologies: Computer Vision, PyTorch, Explainable AI