COCO

4 articles about COCO - tutorials, guides, and insights.

Synthetic Data Object Detection YOLO Dataset Quality Computer Vision MLOps Segmentation Instance Segmentation

From Prompt to mAP: Synthetic Object Detection Workflow

A step-by-step synthetic object detection workflow from prompts to map improvement, covering generation, QA, export formats, and fast iteration loops for 2026.

Object Detection

Dataset Quality

Object Detection Dataset Quality Checklist for Training

Most detection problems are dataset problems. Use this checklist to validate label quality, class design, coverage, leakage, imbalance, and evaluation before scaling.

Segmentation

Instance Segmentation

Segmentation Masks in 2026: Semantic vs Instance Guide

Learn semantic vs instance segmentation, proper mask formats, clean dataset packaging, and practical QA checks to avoid training failures in vision pipelines.

COCO

YOLO

COCO vs YOLO Format: Differences, Conversions, and Best Practices

Understand COCO vs YOLO annotation formats, key differences, conversion pitfalls, and best practices so your object detection datasets stay consistent and train-ready.