The Picsellia Blog

Data Management

How to Reduce Training Data with Self-Supervised Learning

Self-Supervised Learning (SSL) aims to leverage large unlabeled datasets to train capable feature extractors such as CNN or ViT encoders. But what is SSL?

Konstantinos Poulinakis

July 26, 2022

Dataset management

What Is Image Data Augmentation?

To solve the problem of data scarcity, we use data augmentation techniques. But how do you augment image data? We'll go throw this in a simple way.

Haziqa Sajid

July 19, 2022

MLOps

Why Do Classical MLOps Tools Not Fit Computer Vision?

Computer vision pipelines require a set of processes that are exclusive to Computer Vision. This is where CVOps comes to play.

Haziqa Sajid

July 1, 2022

Computer vision

How To Optimize Computer Vision Models For Edge Devices

Learn the best optimization techniques to decrease model size and increase inference speed in computer vision.

Konstantinos Poulinakis

June 30, 2022

Data Management

Data Versioning & Feedback Loop Best Practices

Data versioning is an effective methodology used when running many experiments that entail different data processing techniques. Find our best practices!

Konstantinos Poulinakis

May 30, 2022

Product

How We Built A Dataset Visual Similarity Search Feature

Learn how we built a dataset visual similarity search feature with embeddings and Qdrant.

May 18, 2022

Model monitoring

Key Metrics To Monitor Computer Vision Solutions

In computer vision high-quality training data doesn't ensure high-performing production models. The work begins after deployment, and monitoring is a must.

Haziqa Sajid

April 27, 2022

Data management

Data Management in AI: Key Success Factor

Research reveals that 50% if AI teams is spent in developing AI on training data, and 15% augmenting datasets to optimize processes around training data.

April 19, 2022

MLOps

How to Use Computer Vision in Cancer Research With MLOps

We introduced Picsellia's new features by presenting a cancer cell research real use-case. Learn how we applied computer vision to medical research.

March 29, 2022