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Infrared imaging heats up - Developing automated, AI-enabled infrared imaging systems for plant phenomics could help researchers detect early signs of plant stress


Australia
May 21, 2024

Are plants cool? Not really…


 

In fact, developing automated, AI-enabled infrared imaging systems for plant phenomics could help researchers detect early signs of plant stress.

So Saswat Panda (Research Officer) and Ming-Dao Chia (Technical Officer) at the APPF ANU node in Canberra are celebrating stage one success for their ANU College of Engineering, Computing & Cybernetics (CECC) TechLauncher project to develop AI-enabled forward-looking infrared (FLIR) imaging for phenotyping plants.

The project is a collaboration between APPF and CECC. Saswat and Ming-Dao lead the project for APPF and work with CECC students.

The first phase (AI FLIR Imaging) has automated plant image capture from RGBD and thermal cameras, calibrated the two cameras, and completed dataset creation and labelling using AI. Watch this video to learn more.

Successfully accomplishing these milestones means the team is ready to move onto the next phase, which involves creating 3D thermal point clouds and performing advanced thermal image analysis using machine learning.

Saswat and Ming-Dao thank Dr Richard Poire and Prof. Danielle Way for their support in helping the CECC students understand the impact of technology being developed in plant study.

Thanks also to APPF, the ANU AgriFood Innovation Institute (formerly the Centre for Entrepreneurial Agri-Technology, CEAT)and ANU CECC TechLauncher for their support of this project.

 



More news from: APPN - Australian Plant Phenomics Network


Website: http://www.plantphenomics.org.au/

Published: May 24, 2024

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