Deep learning for ecological monitoring: performance in novel habitats and benefits of varied training data

Posted by Ellen Ditria
On October 26, 2020

By Ellen Ditria, PhD candidate Deep learning has fast become recognised as a powerful data processing tool for ecologists faced with vast amounts of image-based data. The ability of deep learning to accurately detect target species in videos and images unlocks the potential for rapid processing of data that usually requires hours of manual labour. […]

Integrating Artificial Intelligence and Citizen Science can Supercharge Ecological Monitoring

Posted by Marina Richardson
On October 19, 2020

Integrating Artificial Intelligence and Citizen Science can Supercharge Ecological Monitoring By Dr. Eva McClure People often imagine the future of technology, and science fiction has depicted many dystopian futures where artificial intelligence (AI) has taken over human civilisation. While AI surpassing human cognition is still in the realms of science fiction, AI technology and […]

How can computer vision supercharge fish connectivity research?

Posted by Marina Richardson
On October 13, 2020

By Sebastian Lopez-Marcano (@seabassphd) Studying animal movement is crucial. Animal movement research is conducted to monitor ecosystem health, understand ecological dynamics and address management and conservation questions. In marine environments, there are different methods to measure fish movement. From nets, tags and statistical modelling, the use of different techniques are providing us with new information […]