Semantic segmentation of rodent burrows using deep convolutional architectures

Author:

Uzdiaev Mikhail,Astapova Marina,Letenkov Maksim

Publisher

SPIE

Reference18 articles.

1. Rodents in Agriculture: A Broad Perspective

2. Group coverage of burrow entrances and distribution characteristics of desert forest-dwelling Rhombomys opimus based on unmanned aerial vehicle (UAV) low-altitude remote sensing: A case study at the southern margin of the Gurbantunggut Desert in Xinjiang;Ma;Acta Ecologica Sinica,2018

3. THE ANALYSIS OF BURROWS RECOGNITION ACCURACY IN XINJIANG'S PASTURE AREA BASED ON UAV VISIBLE IMAGES WITH DIFFERENT SPATIAL RESOLUTION

4. Identification and Counting of European Souslik Burrows from UAV Images by Pixel-Based Image Analysis and Random Forest Classification: A Simple, Semi-Automated, yet Accurate Method for Estimating Population Size

5. An Algorithm for Detecting the Location of Rodent-Made Holes through Aerial Filming by Drones;Heydari;Archives of Pharmacy Practice,2020

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