What we’re about
SF Bay Area Meetup Group: Where AI pioneers, innovators, and enthusiasts gather to dive into AI trends, expand their network, and gain insights from industry experts while shaping the future of AI together!
Upcoming events (4+)
See all- Network event82 attendees from 37 groups hostingMay 14 - Getting Started with FiftyOne Virtual WorkshopLink visible for attendees
When and Where
May 14, 2025 | 9:00 – 10:30 AM Pacific
About the Workshop
Want greater visibility into the quality of your computer vision datasets and models? Then join us for this free 90-minute, hands-on workshop to learn how to leverage the open source FiftyOne computer vision toolset.
At the end of the workshop you’ll be able to:
- Visualize complex datasets
- Explore embeddings
- Analyze and improve models
- Perform advanced data curation
- Integrations
This workshop will explore the importance of taking a data-centric approach to computer vision workflows. We will start with importing and exploring visual data, then move to querying and filtering. Next, we’ll look at ways to extend FiftyOne’s functionality and simplify tasks using plugins and native integrations. We’ll generate candidate ground truth labels, and then wrap things up by evaluating the results of fine tuning a foundational model.
Prerequisites: working knowledge of Python and basic computer vision concepts.
All attendees will get access to the tutorials, videos, and code examples used in the workshop
- Network event86 attendees from 36 groups hostingMay 20 - Image Generation: Diffusion Models & U-Net WorkshopLink visible for attendees
When and Where
- May 20, 2025
- 6:30 PM to 8:30 PM CET | 9:30 AM to 11:30 AM Pacific
- Workshops are delivered over Zoom
About the Workshop
Join us for a 12-part, hands-on series that teaches you how to work with images, build and train models, and explore tasks like image classification, segmentation, object detection, and image generation. Each session combines straightforward explanations with practical coding in PyTorch and FiftyOne, allowing you to learn core skills in computer vision and apply them to real-world tasks.
In this session, we’ll explore image generation techniques using diffusion models. Participants will build a U-Net-based model to generate MNIST-like images and then inspect the generated outputs with FiftyOne.
These are hands-on maker workshops that make use of GitHub Codespaces, Kaggle notebooks, and Google Colab environments, so no local installation is required (though you are welcome to work locally if preferred!)
Workshop Resources
You can find the workshop materials in this GitHub repository.
About the Instructor
Antonio Rueda-Toicen, an AI Engineer in Berlin, has extensive experience in deploying machine learning models and has taught over 300 professionals. He is currently a Research Scientist at the Hasso Plattner Institute. Since 2019, he has organized the Berlin Computer Vision Group and taught at Berlin’s Data Science Retreat. He specializes in computer vision, cloud technologies, and machine learning. Antonio is also a certified instructor of deep learning and diffusion models in NVIDIA’s Deep Learning Institute.
- Network event24 attendees from 37 groups hostingMay 21 - Advanced Computer Vision Data Curation and Model EvaluationLink visible for attendees
When and Where
May 21, 2025 | 9:00 – 10:30 AM Pacific
About the Workshop
Are you looking for simpler and more accurate ways to perform common data curation and model evaluation tasks for your computer vision workflows?Then this workshop with Harpreet Sahota is for you! In this 90 min hands-on workshop, we’ll show you how to make use of FiftyOne’s panel and plugin framework to learn how to:
- Customize the FiftyOne App to work the way you want to work
- Quickly integrate FiftyOne with new models, datasets, and MLOps tools
- Automate common data curation and model evaluation tasks
- Streamline your computer vision workflows with less code and more clicks
Whether you are a beginner or advanced user of FiftyOne, looking for how to get started with customizing the dozens of existing plugins or interested in creating your own, there will be something for you in this workshop!
Prerequisites
A working knowledge of Python and basic familiarity with FiftyOne. All attendees will get access to the tutorials, videos, and code examples used in the workshop.
- Network event184 attendees from 36 groups hostingMay 22 - AI, ML and Computer Vision MeetupLink visible for attendees
When and Where
- May 22, 2025 | 10:00 AM Pacific
- Virtual - Register for the Zoom
CountGD: Multi-Modal Open-World Counting
We propose CountGD, the first open-world counting model that can count any object specified by text only, visual examples only, or both together. CountGD extends the Grounding DINO architecture and adds components to enable specifying the object with visual examples. This new capability – being able to specify the target object by multi-modalites (text and exemplars) – lead to an improvement in counting accuracy. CountGD is powering multiple products and has been applied to problems across different domains including counting large populations of penguins to monitor the influence of climate change, counting buildings from satellite images, and counting seals for conservation.
About the Speaker
Niki Amini-Naieni is a DPhil student focusing on developing foundation model capabilities for visual understanding of the open world at the Visual Geometry Group (VGG), Oxford supervised by Andrew Zisserman. In the past, Niki has consulted with Amazon and other companies in robotics and computer vision, interned at SpaceX, and studied computer science and engineering at Cornell.
GorillaWatch: Advancing Gorilla Re-Identification and Population Monitoring with AI
Accurate monitoring of endangered gorilla populations is critical for conservation efforts in the field, where scientists currently rely on labor-intensive manual video labeling methods. The GorillaWatch project applies visual AI to provide robust re-identification of individual gorillas and generate local population estimates in wildlife encounters.
About the Speaker
Maximilian von Klinski is a Computer Science student at the Hasso-Plattner-Institut and is currently working on the GorillaWatch project alongside seven fellow students.
This Gets Under Your Skin – The Art of Skin Type Classification
Skin analysis is deceptively hard: inconsistent portrait quality, lighting variations, and the presence of sunscreen or makeup often obscure what’s truly “under the skin.” In this talk, I’ll share how we built an AI pipeline for skin type classification that tackles these real-world challenges with a combination of vision models. The architecture includes image quality control, facial segmentation, and a final classifier trained on curated dermatological features.
About the Speaker
Markus Hinsche is the co-founder and CTO of Thea Care, where he builds AI-powered skincare solutions at the intersection of health, beauty, and longevity. He holds a Master’s in Software Engineering from the Hasso Plattner Institute and brings a deep background in AI and product development.
A Spot Pattern Is like a Fingerprint: Jaguar Identification Project
The Jaguar Identification Project is a citizen science initiative actively engaging the public in conservation efforts in Porto Jofre, Brazil. This project increases awareness and provides an interesting and challenging dataset that requires the use of fine-grained visual classification algorithms. We use this rich dataset for dual purposes: teaching data-centric visual AI and directly contributing to conservation efforts for this vulnerable species.
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. He is currently a Research Scientist at the Hasso Plattner Institute. Since 2019, he has organized the Berlin Computer Vision Group and taught at Berlin’s Data Science Retreat. He specializes in computer vision, cloud technologies, and machine learning. Antonio is also a certified instructor of deep learning and diffusion models in NVIDIA’s Deep Learning Institute.
Past events (34)
See all- Network event199 attendees from 36 groups hostingMay 13 - Object Detection & Instance Segmentation: YOLO in Practice WorkshopThis event has passed