Home » Videos » AI in Wildlife Conservation: How Drones, Sensors & GPS Are Changing Forest Protection | EWA 2026 Can AI and technology transform wildlife conservation in India? At the Eco Warrior Awards 2026 Conclave, leading experts discussed how artificial intelligence, drones, GPS collars, camera…
United Nations. Transforming our world: the 2030 Agenda for Sustainable Development. UN General Assembly Resolution A/RES/70/1 (United Nations, 2015). Convention on Biological Diversity (CBD). Kunming-Montreal Global Biodiversity Framework. Adopted 19 December 2022 at the 15th Conference of Parties to the CBD (Montreal, Canada. (2022). World…
And how AI will change journalistic investigations to come How did The Outlaw Ocean Project use AI in its five-year investigation of the global fishmeal trade? And how AI will change journalistic investigations to come Article 50 of the EU AI…
Factor This HydroWing, the tidal energy division of Inyanga Marine Energy Group, has signed a contract with Ecodetect to introduce AI-driven environmental monitoring solutions to its pioneering tidal stream energy project at Morlais in Wales. “Tidal energy projects operate in…
Heavy machine learning models don't work everywhere, especially not on the edge where computing power... Tagged with python, computervision, edgecomputing, opencv. Heavy machine learning models don't work everywhere, especially not on the edge where computing power is not as good.
The Gulf Fishery-Independent Survey of Habitat and Ecosystem Resources, or G-FISHER, is a video-based fishery-independent survey scientists use to monitor reef fish populations in the Gulf of America. This new StoryMap provides a detailed overview of the program and how…
by Ian Scheffler, University of Pennsylvania edited by Swati Mestri, reviewed by Robert Egan For decades, event cameras, which emulate the biological retina by continuously monitoring changes in light intensity, have promised to revolutionize how robots perceive the world by…
A new deep learning framework segments, classifies and counts microscopic mineral grains with 97.57% accuracy without requiring annotated segmentation masks. Subject of Research: A deep learning framework for classifying and quantifying heavy minerals in microscopic images without annotated segmentation data. News…
The difficulty the authors address stems from three well-known obstacles in the field: the high dimensionality of spectral data, the limited availability of labeled samples, and the need to jointly model spectral and spatial information. The first stage of the…
A systematic review of 94 studies finds that deep learning models, especially GAN-based architectures, outperform classical methods for underwater image and video enhancement, while real-time processing and data scarcity remain unresolved challenges. Subject of Research: A systematic review of conventional and…
Detection, segmentation, multimodal models, and real‑world perception.
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