In this talk we introduce Setmlvis, a novel tool employing set theory and visualization for object detection model comparison. It efficiently aggregates and matches detection data across multiple models, highlighting where models align or diverge in object detection. This approach allows for analysis of each model’s unique capabilities and common strengths. Through our system, we demonstrate how set theory and visualization can be used as a valuable asset in the model evaluation process.

Speaker: Liudas Panavas is a CS PhD student at Northeastern University’s Data Visualization Lab, where they focus on explainable AI for object detection algorithms. They specialize in developing visual analytics software and conducting comprehensive user experience evaluations.

Resource links

* Setmlvis on Pypi: https://pypi.org/project/setmlvis/

* Colab Notebook: https://colab.research.google.com/drive/1-tuGJ9RpCm3ROBjUD2lHiRK2H9Tgoc6V?usp=sharing

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Recorded on Jan 25, 2024 at the AI, Machine Learning and Data Science Meetup.

#computervision #machinelearning #datascience #ai #artificialintelligence

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