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Machine learning

Learn how you can leverage data and algorithms to improve model performance on a set of tasks.
active learning for object detection and human pose estimation
Machine learning

Active learning for object detection and human pose estimation

Explore the application of the Learning Loss for Active Learning algorithms in object detection and human pose estimation tasks within this article on Active Learning.
December 1, 2020
6 min
active Learning for classification models
Machine learning

Active Learning for classification models

We present our implementation of 2 active learning algorithms, their usage in SuperAnnotate's platform, share the code and some benchmarking data.
November 17, 2020
7 min
manage annotation teams during covid
Machine learning

How to effectively manage annotation teams during COVID-19

Learn about the ways SuperAnnotate makes managing annotation teams significantly easier, and how our methods can be applied to the Covid-19 world.
October 2, 2020
6 min
how to detect mislabeled annotations
Machine learning

How to detect 93% of mislabeled annotations while spending 4x less time on quality assurance

Explore the automaation tools within the SuperAnnotate Platform that speed up the quality assurance process substantially.
September 28, 2020
6 min
annotations for aerial imagery
Machine learning

Annotations for aerial imagery: Why pixel precision will be the new norm

Find out more about pixel-precision in aerial imagery, AI segmentation-based approaches, pixelwise annotation, and more.
September 23, 2020
5 min
speed up image labeling using transfer learning
Machine learning

Speed up image labeling using transfer learning: No code required

Scale and automate your annotation process using transfer learning. We share a tutorial on how transfer learning works and how to do it without coding.
September 1, 2020
7 min
accuracy and runtime tradeoff in modern edge detection algorithms
Machine learning

Accuracy and runtime tradeoff in modern edge detection algorithms

How to improve both inference time (2x) and F1 score (by 0.06) of the pruned neural network using knowledge distillation.
August 27, 2020
8 min
u-net based building footprint pre-annotation
Machine learning

U-Net based building footprint pre-annotation

Introducing SuperAnnotate’s U-Net-based building footprint pre-annotation. Follow the link to learn more about the algorithm and code description.
August 12, 2020
3 min

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