The project aims to develop a project leveraging AI to extract a tactical board from Ultimate Frisbee video footage. The goal is to automate the process of analyzing gameplay and generating visual representations of player positions and movements on the field. This project intends to offer coaches and players a tool for tactical analysis and strategic planning based on actual gameplay footage. By employing AI algorithms, the system will identify players and produce a comprehensive overview of the game's dynamics. Ultimately, this endeavor seeks to enhance understanding and strategic decision-making in Ultimate Frisbee.

Hands-on workshop led by Dan Gural, Machine Learning Engineer at Voxel51. The session covers FiftyOne Basics (terms, architecture, installation, and usage), workflows to explore and curate data, and how FiftyOne represents and slices unstructured computer vision data. The second half is a hands-on introduction: loading datasets from the FiftyOne Dataset Zoo, navigating the FiftyOne App, programmatically inspecting attributes, adding samples and custom attributes, generating and evaluating model predictions, and saving insightful views. Prerequisites: working knowledge of Python and basic computer vision. Attendees will gain access to tutorials, videos, and code examples used in the workshop.

FiftyOne Basics (terms, architecture, installation, and general usage); overview of useful workflows to explore, understand, and curate your data; how FiftyOne represents and semantically slices unstructured computer vision data

In the first part of the workshop, we cover FiftyOne basics (terms, architecture, installation, and general usage), plus an overview of useful workflows to explore, understand, and curate your data, and how FiftyOne represents and semantically slices unstructured computer vision data.

A 90-minute hands-on workshop to learn how to leverage the FiftyOne computer vision toolset. Topics include FiftyOne basics (terms, architecture, installation), an overview of useful workflows to explore, understand, and curate data, and how FiftyOne represents and semantically slices unstructured CV data. The second half provides a hands-on introduction to FiftyOne: loading datasets from the FiftyOne Dataset Zoo, navigating the FiftyOne App, programmatically inspecting dataset attributes, adding new samples and custom attributes, generating and evaluating model predictions, and saving insightful views.

A 90-minute hands-on workshop on the FiftyOne computer vision toolset. Part 1 covers FiftyOne Basics (terms, architecture, installation, and general usage), an overview of useful workflows to explore, understand, and curate data, and how FiftyOne represents and semantically slices unstructured computer vision data. Part 2 is a hands-on introduction to FiftyOne where you load datasets from the FiftyOne Dataset Zoo, navigate the FiftyOne App, programmatically inspect attributes of a dataset, add new samples and custom attributes, generate and evaluate model predictions, and save insightful views into the data. Prerequisites: working knowledge of Python and basic computer vision.

A 90-minute hands-on workshop led by Dan Gural on using FiftyOne for computer vision datasets and models. Part 1 covers FiftyOne basics (terms, architecture, installation, and general usage) and useful workflows to explore, understand, and curate data; Part 2 provides a hands-on introduction to FiftyOne (load datasets from the FiftyOne Dataset Zoo, navigate the FiftyOne App, inspect attributes, add new samples and custom attributes, generate and evaluate model predictions, and save insightful views).

A 90-minute hands-on workshop exploring the FiftyOne computer vision toolset. Part 1 covers FiftyOne Basics (terms, architecture, installation, and general usage), an overview of useful workflows to explore, understand, and curate your data, and how FiftyOne represents and semantically slices unstructured computer vision data. Part 2 provides a hands-on introduction to FiftyOne: loading datasets from the FiftyOne Dataset Zoo, navigating the FiftyOne App, programmatically inspecting attributes, adding new samples and custom attributes to a dataset, generating and evaluating model predictions, and saving insightful views into the data. Prerequisites: working knowledge of Python and basic computer vision. Attendees get access to the tutorials, videos, and code examples used in the workshop.

It is an innovative application that enables users to scan exhibition press texts, typically written in International Art English—a unique and often criticized jargon prevalent in the contemporary art world, noted for its complex, abstract vocabulary and a style distinct from everyday language. Using a smartphone camera, the app simplifies these texts into a single, easily comprehensible sentence. Additionally, ArtSpeak Simplifier analyzes the accompanying image (often a central piece of the exhibition) and succinctly describes it in one sentence.

PersonaPix revolutionizes the perception of personality traits from images, targeting applications in social media, business, and dating. By integrating psychological personality modeling with computer vision techniques like contrastive learning and aesthetic image analysis, it offers an insightful analysis of visual cues. This innovative tool empowers users with enhanced self-awareness and enriched digital impact of their visual presence.

Hands-on workshop to learn how to leverage the FiftyOne computer vision toolset. Topics include FiftyOne Basics (terms, architecture, installation, and general usage); overview of useful workflows to explore, understand, and curate data; how FiftyOne represents and semantically slices unstructured computer vision data. The second half is a hands-on introduction to FiftyOne, where you will learn how to load datasets from the FiftyOne Dataset Zoo, navigate the FiftyOne App, programmatically inspect attributes, add new samples and custom attributes, generate and evaluate model predictions, and save insightful views into the data.

A 90-minute hands-on workshop on the FiftyOne computer vision toolset. Part 1 covers FiftyOne Basics (terms, architecture, installation, and general usage), useful workflows to explore, understand, and curate data, and how FiftyOne represents and semantically slices unstructured computer vision data. Part 2 is a hands-on introduction to FiftyOne: load datasets from the FiftyOne Dataset Zoo, navigate the FiftyOne App, programmatically inspect attributes, add new sample and custom attributes to a dataset, generate and evaluate model predictions, and save insightful views into the data. Prerequisites: working knowledge of Python and basic computer vision. Attendees will gain access to tutorials, videos, and code examples used in the workshop.

A 90-minute hands-on workshop covering FiftyOne basics, workflows to explore and curate data, and how FiftyOne represents unstructured computer vision data, followed by a practical session to load datasets from the FiftyOne Dataset Zoo, navigate the FiftyOne App, programmatically inspect attributes of a dataset, add new samples and custom attributes, generate and evaluate model predictions, and save insightful views into the data.

Two-part workshop led by Dan Gural. Part 1 covers FiftyOne basics (terms, architecture, installation, general usage), an overview of useful workflows to explore, understand, and curate data, and how FiftyOne represents and semantically slices unstructured computer vision data. Part 2 is a hands-on introduction to FiftyOne: loading datasets from the FiftyOne Dataset Zoo, navigating the FiftyOne App, programmatically inspecting attributes, adding new samples and custom attributes, generating and evaluating model predictions, and saving insightful views into the data. Prerequisites: working knowledge of Python and basic computer vision. Attendees will gain access to tutorials, videos, and code examples used in the workshop.

A 90-minute hands-on workshop by Dan Gural (machine learning engineer, Voxel51) covering FiftyOne basics, useful workflows to explore and curate data, and how FiftyOne represents and semantically slices unstructured computer vision data, followed by a hands-on session to load datasets from the FiftyOne Dataset Zoo, navigate the FiftyOne App, inspect attributes programmatically, add samples and custom attributes, generate and evaluate model predictions, and save insightful views. Prerequisites: working knowledge of Python. Attendees get access to the tutorials, videos, and code examples used in the workshop.

A 90-minute hands-on workshop led by Leila Kaneda, Machine Learning Engineer at Voxel51. Part 1 covers FiftyOne Basics (terms, architecture, installation, and general usage) and an overview of useful workflows to explore, understand, and curate your data, plus how FiftyOne represents and semantically slices unstructured computer vision data. The second half is a hands-on introduction to FiftyOne: loading datasets from the FiftyOne Dataset Zoo, navigating the FiftyOne App, programmatically inspecting attributes of a dataset, adding new samples and custom attributes, generating and evaluating model predictions, and saving insightful views into the data. Prerequisites: working knowledge of Python.

Learning Journey - Session 4 of the Certification Study Group for Google Cloud Professional Machine Learning Engineer certification. Speakers: Roya Kandalan (Senior Research Scientist, Aware, Inc.); Maddie Shang (Sr. AI Research Engineer, OpenMined); Linda Kovacs (Software Engineer, Accenture).

A 90-minute hands-on workshop led by Jacob Marks, PhD (Voxel51), introducing the FiftyOne open-source computer vision toolset. Part 1 covers FiftyOne basics (terms, architecture, installation, and general usage), useful workflows to explore, understand, and curate data, and how FiftyOne represents and semantically slices unstructured data. Part 2 is a hands-on introduction to FiftyOne, including loading datasets from the FiftyOne Dataset Zoo, navigating the FiftyOne App, programmatically inspecting attributes, adding new samples and custom attributes, generating and evaluating model predictions, and saving insightful views.

Workshop covering Foundations of Machine Learning and Deep Learning; Medical Imaging and Computer Vision; Video Processing and Pose Estimation; Comprehensive Project Work and Integration.

Foundations of Machine Learning and Deep Learning; Medical Imaging and Computer Vision; Video Processing and Pose Estimation; Comprehensive Project Work and Integration