Learning to Compare: A Visual Guide to Metric Learning for Wildlife Re-ID
An intuition-first, visual guide to metric learning — how machines learn to tell individual animals apart for conservation re-identification.
12 Posts
Ai
Racing Models, Not Opinions: How We Ran Wildfire ML R&D for Pyronear
How a literature survey, self-contained experiments, and a shared leaderboard turned 28 research papers into a production smoke verifier with 4x fewer false alarms.
Smoke Is a Behavior: Inside Pyronear's Temporal Wildfire Detection Model
How the temporal smoke verifier works, step by step — detection boxes become tubes, stabilized crops make motion legible, and a vision transformer plus a tiny temporal head learn that smoke grows and drifts.
Identify individuals with Local Feature Matching
A comprehensive examination of using local feature matching for individual identification.
How to prepare data for identification?
An in-depth look at the common preprocessing stages required to perform identification using computer vision.
Tracking the Journey: How to Monitor Wild Salmon Migrations
An in-depth look at the systems developed and deployed to track the journey of wild salmon as they return to their natal streams.
Protecting the Forest: Building an early forest fire detector
Detecting early forest fires in real time using low powered technology
How to detect elephant rumbles at scale
Learn how to leverage audio processing to localize elephant rumbles on terabytes of data.
A guide to designing a bear face recognition system
Identify bears with Metric Learning.
A guide to designing a bear face segmentation system
Detecting bears in real time using low-power technology.
How to build a benthic coral reefs analyser
Learn how to successfully train a computer vision model to accurately analyse underwater benthic imagery.
How to build a real time bear detection system
Detecting bears in real time using low-power technology.