Whether it’s for facial recognition, content-based image retrieval, or recommendation systems, the ability to search for similar vectors quickly and … More
Category: Machine Learning
How to Find False Negatives in Facial Recognition with Neo4j
Current cutting-edge facial recognition models offer human-level accuracy. Still, we can improve facial recognition model accuracies if we represent classifications … More
Decide Whom Your Child Looks Like with Facial Recognition: Mommy or Daddy?
Parents do discuss whom their child is looking like but no one can really be convinced about the result with … More
How to Find False Positives in Facial Recognition with Neo4j
Facial recognition models already reached and passed human level accuracy. Still, these cutting-edge models do some clear mistakes when verifying … More
Normalization for Facial Recognition with MediaPipe
Detection and alignment are important early mandatory stages of a modern facial recognition pipeline. However, face detection depends on extracting … More
Virtual Background with Mediapipe
Are you using virtual backgrounds in your online meetings? The answer is probably yes. We can join meetings with such … More
Deep Face Detection with Mediapipe
Mediapipe is a Google powered machine learning solution covering face detection task as well. It focuses on live and streaming … More
A Gentle Introduction to Student’s T-Test
Guinness is a tasty dark stout beer. It contributed a fundamental tool in science and statistics beyond its taste. In … More
Gradient Boosting vs Adaboost
Boosting makes decision trees cool again. Here, gradient boosting and adaboost are the most common boosting techniques for decision tree … More
Random Forest vs Gradient Boosting
Tree-based algorithms are very promising in daily data science problems but their some extended adaption makes them so popular nowadays. … More
