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• Drone Pilot Training with Wildlife Drones (Australia)

Ever wanted to become a Drone Pilot? Here is your chance!

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• News: The Latest in Conservation Tech

<p>Check out this round-up of three of the latest news stories from the conservation tech world. </p> <p><a href="https://wildlabs.us11.list-manage.com/subscribe/post?u=13a5323dc43234ee66d95cc90&id=fce1034265">See more conservation tech news by subscribing to our bi-monthly digest. </a></p>

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• Identification of Wildlife in Camera Trap Images

<p>Camera trap wildlife surveys can generate vast amounts of imagery. A key problem in the wildlife ecology field is that vast amounts of time is spent reviewing this imagery to identify the species detected. Valuable resources are wasted, and the scale of studies is limited by this review process. The use of computer software capable of extracting false positives, automatically identifying animals detected and sorting imagery could greatly increase efficiency. AI has been demonstrated as an effective option for automatically identifying species from camera trap imagery. Currently available code bases are inaccessible to the majority of users; requiring high-performance computers, advanced software engineering skills and, often, high-bandwidth internet connections to access cloud services. The <em>ClassifyMe</em> software tool is designed to address this gap and provides users the opportunity to utilise state-of-the-art image recognition algorithms without the need for specialised computer programming skills. <em>ClassifyMe</em> is IDEAL for field researchers, allowing users to sweep through camera trap imagery using field computers instead of office-based workstations.</p>

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• New Paper: Comparative Analysis of Multi-Platform, Multi-Resolution, Multi-Temporal LiDAR Data for Forest Inventory

This study presents a comprehensive comparison of point clouds from four systems, linear and Geiger-mode LiDAR from manned aircraft and multi-beam LiDAR on unmanned aerial vehicle (UAV), and in-house developed Backpack, with the consideration of different forest canopy cover scenarios.

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• New preprint: Towards automatic detection of wildlife trade using machine vision models

Authors: Ritwik Kulkarni, Enrico Di Minin