#Image Segmentation

Articles about Image Segmentation — exploring patterns, best practices, and real-world implementations in production systems.

1 post tagged with image segmentation. ← All posts

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Pratik Dhanave · ·6 min read

Object Detection and Segmentation — Beyond "What Is This?"

Classifying a whole image as "cat" is only the beginning of computer vision. Real applications need to know where the cat is, how many objects there are, and sometimes exactly which pixels belong to each one. Object detection and segmentation answer those harder questions, and they power self-driving cars, medical imaging, and photo editing. This post covers the main vision tasks beyond classification and how they build on the CNN foundation.

Real vision needs more than 'what is this?' — the task hierarchy runs classification → detection (bounding boxes) → semantic segmentation (per-pixel) → instance segmentation. How one-stage (YOLO) vs two-stage detectors and encoder-decoders (U-Net) build on the CNN backbone, powering self-driving and medical imaging.

#Computer Vision#Object Detection#Image Segmentation#Deep Learning#Machine Learning

All posts on this site are written by Pratik Dhanave, an Agentic AI Architect with 7+ years building production distributed systems, multi-agent AI platforms, and cloud-native infrastructure. About the author → Each article includes working code, architecture diagrams, and references to the specific frameworks and standards discussed. Browse all posts or explore related topics using the tag cloud above.