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SUMMARY:Telling Tree Stories through Laser Scans and AI - Stefano Puliti\,
  Norwegian Institute of Bioeconomy Research
DTSTART:20231124T130000Z
DTEND:20231124T140000Z
UID:TALK204436@talks.cam.ac.uk
CONTACT:114742
DESCRIPTION:Recent technological advancements in laser scanning have enabl
 ed the capture of high-resolution three-dimensional (3D) forest scenes\, m
 arking a significant shift in forest management towards sustainability. Th
 is presentation highlights the intersection of these cutting-edge laser sc
 anning techniques with the evolving field of deep learning\, emphasizing t
 heir combined potential in revolutionizing forest mapping and analysis. Th
 e focus is on recent developments in deep learning methodologies applied t
 o 3D forest data and the exploration of machine learning-ready datasets th
 at facilitate detailed\, tree-level analysis. Specifically\, we will delve
  into the application of deep learning algorithms for critical 3D point cl
 oud tasks\, such as tree instance segmentation\, forest scene panoptic seg
 mentation\, and tree species classification. These advancements not only e
 nable a more granular understanding of forest ecosystems at an individual 
 tree level but also open avenues for optimizing biomass production and sto
 ck management while preserving vital ecosystem functions. This confluence 
 of high-resolution 3D data acquisition and sophisticated deep learning app
 roaches represents a transformative approach to sustainable forest managem
 ent\, promising significant contributions to both ecological conservation 
 and resource optimization.\n\nStefano is a research scientist at the Norwe
 gian Institute of Bioeconomy research doing research on the use of proxima
 l laser scanning and deep learning for capturing individual tree propertie
 s and applying this information to forest management.
LOCATION:FW11\, William Gates Building. Zoom link: https://cl-cam-ac-uk.zo
 om.us/j/4361570789?pwd=Nkl2T3ZLaTZwRm05bzRTOUUxY3Q4QT09&amp\;from=addon 
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