Welcome to our Blog!

Computer Vision

Top 10 GT Studio Features That Simplify Semantic Segmentation For Machine Learning

Discover GT Studio features that make semantic segmentation simpler and more accurate for ML teams.
Continue Reading
Computer Vision

Your Complete Guide To Image Segmentation

Understanding different types of segmentation with examples. BONUS: Free access to GT Studio for your next ML initiative!
Continue Reading
Computer Vision

Video Annotations For Deep Learning — Popular Applications and Examples

Discover different types of video annotations, popular use cases, and high-precision tools for computer vision and deep learning.
Continue Reading
Computer Vision

8 Instant Benefits of Switching To A Mature Data Labeling Platform

Mature, high-performing labeling tools make all the difference in data quality for ML models. Explore features of GT Studio — our web-based data annotation platform that will instantly turn your labeling game around for free.
Continue Reading
Computer Vision

Image Annotation For Computer Vision — The Ultimate Guide With Data Samples

Discover different types of image annotations, popular use cases, and high-precision tools for computer vision.
Continue Reading
Computer Vision

Building Training Datasets For Your ML Model? Here’s Everything You Need To Know...

Structured training data is quickly becoming the currency of new-age machine AI innovations and so we decided to break down the anatomy of a good training dataset to brush up on basics.
Continue Reading
Computer Vision

Decision Framework For Data Labeling Strategy

Busting common misbeliefs about data labeling workflows and budgets to provide a realistic decision framework that will take your data labeling strategy from flawed to flawless.
Continue Reading
Computer Vision

List of LiDAR Datasets for Autonomous Vehicles Till 2018

Although 2D camera data is used to teach autonomous vehicles to find their way from Point A to PointB, it comes with its own set of drawbacks. For eg: camera images are not very useful when it is dark or there are reflections due to strong sunlight
Continue Reading
Computer Vision

Loss Functions for Computer Vision Models

Machine learning algorithms are designed so that they can “learn” from their mistakes and “update” themselves using the training data we provide them. But how do they quantify these mistakes?
Continue Reading