CV Brief · Sunday, 6 September 2026
CV Brief
Tutorials & Guides
FPN Explained: Multi-scale object detection for tiny objects
Feature Pyramid Networks break down how neural networks detect objects across different scales, critical for real-world detection pipelines handling variable object sizes. Essential reading for anyone tuning YOLO or Faster R-CNN for production workloads.
Read more →How CNNs actually see: pixels, kernels, convolution mechanics
Deep dive into CNN internals from first principles—pixels through learned filters to final outputs. Practical foundation for debugging model behavior and making informed architecture choices in your CV pipeline.
Read more →Industry & Deployments
Machine vision internals: what happens when AI reads images
Explores frame-level image processing and how models interpret visual input, relevant for video processing pipelines and understanding latency in real-time systems. Bridges theory and practical deployment concerns.
Read more →Auto-labeling confidence threshold: don't use 0.5. For quality training data, start at 0.7 and manually review the 0.5–0.7 band. The borderline cases are where your model learns.