Düsseldorf AI, ML & Computer Vision Meetup – Feb 4, 2025

Düsseldorf AI, ML & Computer Vision Meetup – Feb 4, 2025

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Düsseldorf AI, ML and Computer Vision Meetup

Feb 4, 2025 | 5:00 to 8:00 PM

Register for the event at Impact Hub Düsseldorf

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Date, Time and Location

Date and Time

Feb 4, 2025 from 5:00 PM to 8:00 PM

Location

The Meetup will take place at Factory Campus, Gatherweg 69  Pioneer building, 4th Floor, Skyline conference room in Düsseldorf.

How Language and Foundation Models can Support Vision Tasks in the Context of Autonomous Driving

Jochen Schroeer
Microsoft

This presentation explores the integration of language and foundation models to enhance vision tasks in autonomous driving. By leveraging advanced AI techniques, we can improve scene understanding, and decision-making processes, e. g. to cover long-tail scenarios in driving situations.

About the Speaker

Jochen Schroeer is a Principal Architect – Mobility and Lead Architect AVOps (Autonomous Vehicle Operations) at Microsoft.

When Images Look Alike - Mastering Perceptual and Exact Deduplication

Antonio Rueda-Toicen
Hasso Plattner Institut

Explore techniques for detecting duplicate and similar images at scale, from neural network embeddings and efficient quantization to perceptual and cryptographic hashing. Learn practical approaches for dataset cleaning, with focus on balancing accuracy and computational costs for large-scale deduplication.

About the Speaker

Antonio Rueda-Toicen, an AI Engineer in Berlin, has extensive experience in deploying machine learning models and has taught over 300 professionals. Since 2019, he has organized the Berlin Computer Vision Group and, since 2024, the AI Maker Community at Hasso Plattner Institut (HPI). He specializes in computer vision, cloud technologies, and machine learning. Antonio is also a certified instructor of deep learning in Nvidia’s Deep Learning Institute.

How to Make the Best Self-Driving Dataset

Dan Gural
Voxel51

AV/ADAS is one of the most advanced fields in Visual AI. However, getting your hands on a high quality dataset can be tough, let alone working with them to get a model to production. In this talk, I will show you the leading methods and tools to help visualize as well take these datasets to the next level. I will demonstrate how to clean and curate AV datasets as well as perform state of the art augmentations using diffusion models to create synthetic data that can empower the self driving car models of the future,

About the Speaker

Daniel Gural is a seasoned Machine Learning Engineer at Voxel51 with a strong passion for empowering Data Scientists and ML Engineers to unlock the full potential of their data.

Dataset Safari: Adventures from 2024's Top Computer Vision Conferences

Harpreet Sahota
Voxel51

Datasets are the lifeblood of machine learning, driving innovation and enabling breakthrough applications in computer vision and AI. This talk presents a curated exploration of the most compelling visual datasets unveiled at CVPR, ECCV, and NeurIPS 2024, with a unique twist – we’ll explore them live using FiftyOne, the open-source tool for dataset curation and analysis.

Using FiftyOne’s powerful visualization and analysis capabilities, we’ll take a deep dive into these collections, examining their unique characteristics through interactive sessions. We’ll demonstrate how to:

  • Analyze dataset distributions and potential biases
  • Identify edge cases and interesting samples
  • Compare similar samples across datasets
  • Explore multi-modal annotations and complex label structures

Whether you’re a researcher, practitioner, or dataset enthusiast, this session will provide hands-on insights into both the datasets shaping our field and practical tools for dataset exploration. Join us for a live demonstration of how modern dataset analysis tools can unlock deeper understanding of the data driving AI forward.

About the Speaker

Harpreet Sahota is a hacker-in-residence and machine learning engineer with a passion for deep learning and generative AI. He’s got a deep interest in RAG, Agents, and Multimodal AI.