Tag: Voxel51

Voxel51 Releases Computer Vision Industry’s First Open-Source Rapid Data Experimentation Tool
Engineering, Software

Voxel51 Releases Computer Vision Industry’s First Open-Source Rapid Data Experimentation Tool

Ann Arbor startup and TechDisrupt 2019 AI top pick Voxel51 just announced that it has just launched a new tool called FiftyOne, the computer vision industry’s first open-source tool for experimenting with and cleaning image and video data for machine learning. Engineers working with machine learning for image and video data sets have a new way of inspecting their data for labeling errors and finding explanations for functional problems emerging from the data. It’s a quicker solution to the problem of cleaning datasets, which grows by the year along with the size of datasets available for machine learning applications.

Voxel51 Releases COVID-19 Physical Distancing Impact Trend Analysis Tool
Announcements, Software

Voxel51 Releases COVID-19 Physical Distancing Impact Trend Analysis Tool

Ann Arbor’s Voxel51, which offers advanced machine learning tools to analyze video, has just released a tool that looks at the social impact of physical distancing from the COVID-19 epidemic. They’re calling it PDI, or Physical Distancing Index. The data can be used in a number of ways to look at the results of social distancing orders and correlated with virus spread trends.

Voxel51 Chosen As AI Top Pick To Present at Tech Disrupt 2019
Mobility Tech, News, Software

Voxel51 Chosen As AI Top Pick To Present at Tech Disrupt 2019

Ann Arbor’s Voxel51, an AI startup that analyzes video for self-driving automotive applications and more, was featured last week in TechCrunch for its seed funding round raising $2 million, and because the company was chosen as a top 5 AI/machine learning company across the U.S. selected as a TechCrunch Top Pick to present at Tech Disrupt 2019. AI is growing up, and startups like Voxel51 are getting out there. That’s because Voxel51 is using adaptive tech to analyze videos using AI, not just traditionally frame by frame, but through analyzing the relationships between frames to understand what is going on content-wise over time.

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