Discover how AI-powered semantic segmentation of drone imagery helps detect and map invasive European Water Chestnut colonies, transforming large aerial orthophotos into GIS-ready vegetation maps.
Removing unwanted objects from an image is easy to describe but hard to do well. This article explores how Sairone integrated a LaMa-based inpainting pipeline through IOPaint — using an image and a binary mask to reconstruct missing regions while preserving the surrounding scene, and how mask quality shapes the final result.
Real-world OCR rarely deals with clean, perfectly aligned text. This article explores how PaddleOCR's PP-OCRv5 pipeline handles text detection, recognition, multilingual documents, and complex layouts — and how its modular design lets OCR work as one stage of a larger AI pipeline rather than a standalone tool.
Adding a new object class to a detection system usually means collecting and annotating thousands of images before training can even start. This article explores how prompt-based vision models can generate initial annotations from raw images — letting human annotators review and refine instead of labeling from scratch — and how this workflow is coming soon to the Sairone annotation platform.
This technical report compares Transformer-based pose estimation against traditional approaches, revealing where Vision Transformers truly excel and where they still struggle in practical deployments.
A scalable AI pipeline that uses UAV imagery and semantic segmentation to accurately detect and monitor invasive Phragmites australis in wetland ecosystems.