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Expanding a Human Pose Dataset to Augment a Manufacturing Vision Platform

Invisible AI, a vision platform for manufacturing companies, partnered with...

Reducing Model Error with Data Labeling for Sports AI

An AI sports analytics company used Alegion’s managed service to scale up a...

Global Impact Partnerships Enable Enterprise Machine Learning Projects

The partnership has provided data annotation jobs for Kenyan workers, while...

Product Update: Enhanced Image Annotation Tools Including SmartPoly One-Click Segmentation

This product update features enhanced image annotation capabilities and a n...

The Keypoint: Issue 3

Alegion Newsletter - The Keypoint : Issue #3

Choosing a data labeling partner

In this guide, we walk you through the steps & provide a checklist with all...

Online Learning Techniques: An Overview

Video object detection has several unique challenges. One of the main probl...

Alegion Names Jeff Henry as Chief Revenue Officer

Alegion adds Chief Revenue Officer Jeff Henry to drive ongoing growth in le...

In Defense of Humans - the Fact vs. Fiction of Labeling Automation

The capabilities of ML and AI platforms are constantly evolving, and we spe...

Better Quantifying The Performance Of Object Detection In Video

Video object detection has several unique challenges. One of the main probl...

Single Object Tracking Using The Siamese Family Of Trackers

One of the most challenging tasks in computer vision? Accurate object track...

Tips for Using Alegion Control as a Self-Managed Video Annotation Service

Tutorials and project features giving you a behind the scenes look at the t...

Pixel Tolerance vs. IOU - Which One Should You Use for Quality Training Data?

The purpose of data annotation for computer vision is to teach a model how ...

Alegion Teams with Malaysian Government Agency to Expand ML Workforce Opportunities

Alegion and Malaysian government agency Yayasan Peneraju collaborate to tra...

Welcome to The Keypoint

Welcome to The Keypoint - a newsletter from Alegion updating our customers ...

Investment Banking Veteran and Software Market Strategist Jonathan Price Joins Alegion’s Board of Directors

Investment Banking Veteran and Software Market Strategist Jonathan Price Jo...

Calling All Data Scientists - Survey for Alegion 2021 State of the Industry

Each year, Alegion releases our analysis of the AI / ML space. We call upon...

Dr. Carla Brodley Joins Alegion’s Board of Directors

Renowned Machine Learning Researcher and Inclusive Computing Leader Dr. Car...

A Step-by-Step Guide to Quality Training Data for Computer Vision

Alegion specializes in high-quality training data for computer vision. In t...

How Alegion Stacks Up Against the VA Competition

How will you know if you have the best video annotation solution on the mar...

Active Learning: What it is & How Alegion Does it

Active learning is a method used in machine learning that helps focus data ...

Part 3: Building a Video Annotation Platform

With the rise of video, Alegion has become the top vendor for video annotat...

Part 2: Building a Video Annotation Platform

With the rise of video, Alegion has become the top vendor for video annotat...

Part 1: Building a Video Annotation Platform by Chip Ray, CTO

Over the past year, Alegion has taken on the challenge of building the best...

Alegion Closes Record Year Naming New Executives to Key Leadership Roles

Alegion Inc., a leading training data provider, closes record year naming n...

Designing for Video Annotation

Alegion opens up its powerful data labeling platform for self-serve use wit...

Alegion Control - The New Self Serve Data Labeling Platform

Alegion opens up its powerful data labeling platform for self-serve use wit...

Alegion Welcomes A New CEO!

Alegion Inc., a leading training data provider, announces David Mather, a t...

Entity Groups - Purpose-Built Annotation Tooling

Entity Groups organizes all of the items to be annotated for a particular t...

Alegion Launches ML-assisted Annotation for high-definition, long-running video footage

Alegion Launches ML-assisted Annotation for high-definition, long-running v...

Managing Incident Response Like A Pro

Learn about our incident response best practices collected and implemented ...

CV Case Study: Complex Video Annotation For Loss Prevention

Learn how Alegion helps companies leverage high-precision video annotation ...

Data Labeling for AI & ML Experimentation

This post shows how more experiments & smaller volumes of data help high-pe...

SmartPoly - Empowering Annotators with ML

SmartPoly takes the extreme points of an object in image or video as input ...

How ML Improves Quality

Balancing ML innovations and human expertise to deliver the highest quality

CV Case Study: Subjective Scene Classification for Improved Search Experience

This CV case study shows how Alegion built a scalable data labeling pipelin...

A Platform Built for Quality

This short guide shows how Alegion's Platform can improve your data labelin...

ML Experimentation - Fail Fast, Learn Faster

In this episode, Saurabh and I talk to Alegion’s Chief Data Scientist, Cher...

Alegion Flex Launch

Alegion Flex is the first ML data labeling solution designed for ML experim...

How Alegion Guarantees Quality

This white paper shows how Alegion is able to guarantee quality through our...

CV Case Study: Tracking Attentiveness & Emotion

This case study shows how leveraging high-precision data annotation empower...

Faster R-CNN: Using Region Proposal Network for Object Detection

This article explores Faster R-CNN & how RPNs, fully convolutional networks...

Ai & ML in the 2010s - From Science Fiction to Reality

The 2010s was the decade that “machine intelligence” made the leap from sci...

Cost Of Poorly Labeled Data

Download this complimentary white paper to learn what causes poor quality t...

Checklist for Choosing a Platform

This short guide and accompanying checklist will help you when choosing the...

How to Improve Quality

Download this short complimentary guide to improve your data labeling quali...

NeurIPS 2019 Review - Insider's Guide

In this episode, Alegion’s Chief Data Scientist, Cheryl Martin, and Directo...

How To Measure Quality Data Labeling

This short guide will walk you through the four core metrics to measure you...

Data Science for Business

No BiAS is on the Top 10 AI Podcasts & Radio You Must Follow in 2019! Check...

How To Define Quality Data Labeling

This short guide will help you establish an unambiguous set of rules that d...

How to Achieve Quality Data Annotation

Alegion's Data Science Team put together a whitepaper on annotation guideli...

CV & ML - Visual Understanding Beyond Object Recognition

CV is everywhere! From Snapchat filters to YouTube video buffering to medic...

Alegion ranked #1 place to work

We are excited and honored to be named the #1 place to work among small com...

New Use Cases & Highlights from ICCV 2019

ICCV is a hotbed of innovative ideas and technology aimed at giving the gif...

Methods of Video Annotation

Annotated videos hold the future for training computer vision models. Learn...

Deep Learning for Object Detection Part II

Introduction to a more in depth piece about Fast R-CNN and the innovations ...

Episode 4: Bias in ML

In this podcast episode, we discuss helpful mathematical bias and examples ...

5 Key takeaways from Trade show season

Trade show season has begun and these conferences continually demonstrate t...

Machine Learning for the Enterprise

This emerging world of AI runs on data. Learn how to properly prepare your ...

Deep Learning for Object Detection Part I

Introducing a new series on state-of-the-art object detection techniques an...

New Episode: Supervised vs Unsupervised learning

In this episode we break down the strengths and weaknesses of each approach...

NLP Part II: Understanding the challenges of NLP through Wittgenstein

Philosopher Ludwig Wittgenstein's insights into human communication can hel...

NLP Part I: Communication is Key

As difficult as it can be to successfully communicate with another person, ...

Is data the new oil?

In the latest episode of our podcast, No BiaS, Melody, Nikhil, and Saurabh ...

Just the Cliffnotes - Supervised vs unsupervised learning

New executive summary - “Machine Learning” — Gives “computers the ability t...

Alegion in WSJ & Forbes!

The Wall Street Journal and Forbes take notice that manually labeling data ...

Agriculture is deep into machine learning

ML is revolutionizing agriculture. The benefit to growers is faster, more p...

Supervised vs Unsupervised Learning

What we learned attending 5 AI/ML conferences in June! And a new “how to” ...

New survey shows ai and ml are still nascent

Breaking news: A global survey shows AI is still in its infancy and poor da...

What does Alegion do?

What does Alegion do? O'Reilly AI Conference this week. We prepare quality ...

7 tips to being AI ready

7 tips to being AI ready. We produce quality training data for computer vis...

Measurement bias

If the images your algorithm is learning from were shot with a lens with a ...

The Agile AI Way - part 2

Much like with traditional software development, as AI and ML initiatives t...

The Agile AI Way - part 1

In waterfall these interdependencies aren’t fully explored until the penult...

Sample Bias

With sample bias in machine learning in computer vision, natural language p...