YOLOv9-Based Detection of Diseases in Poplar Trees Using Histogram Equalization and Computer Vision
Fazliddin Makhmudov, Kudratjon Zohirov, Jura Kuvandikov, Zavqiddin Temirov, Akmalbek Abdusalomov Bobomirzayevich, Mukhriddin Mukhiddinov, Khodisakhon Muraeva, Jasur Sevinov, Furkat Bolikulov · 2026
Read YOLOv9-Based Detection of Diseases in Poplar Trees Using Histogram Equalization and Computer Vision by Fazliddin Makhmudov, Kudratjon Zohirov, Jura Kuvandikov, Zavqiddin Temirov, Akmalbek Abdusalomov Bobomirzayevich, Mukhriddin Mukhiddinov, Khodisakhon Muraeva, Jasur Sevinov, Furkat Bolikulov (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13259278.txt.
Description
Fazliddin Makhmudov and coauthors detect poplar leaf diseases from photos in a 2026 study. Hand collected images from Uzbekistan and South Korea cover four common diseases, including scab and rust. The image set will be released publicly as the first dedicated poplar disease collection.
Contrast boosting through histogram equalization prepared images for the detection model. A recent YOLO family model then classified the disease patterns. Geographic variety in the photos supports wider use beyond one region. Early detection helps protect trees valued for timber, paper, windbreaks, and carbon storage. Forest managers gain both data and a scalable monitoring method.
Catalog record
| CREATOR | Fazliddin Makhmudov, Kudratjon Zohirov, Jura Kuvandikov, Zavqiddin Temirov, Akmalbek Abdusalomov Bobomirzayevich, Mukhriddin Mukhiddinov, Khodisakhon Muraeva, Jasur Sevinov, Furkat Bolikulov |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 44 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |