Abstract
The workshop investigated the potential of machine learning and most specifically deep learning techniques to the understanding of soils characteristics and behavior from various scales and horizons (above-aerial, and inside -CT-scan) through three lecturers. The attendees could provide several perspectives of deep learning techniques applications to a range of problems and images notably:
i) in marine, forestry and farming environment from aerial perspective;
ii) for CT-scan image segmentation; in a multi-scale sensing and image analysis point of view;
iii) 3D morphological and textural analysis of voxels datasets
iv) Micro-Macro scale issue and its modeling
v) Deep learning+Computer Vision in the context of New Zealand environment
vi) Multi-Scale UAV Mapping of surface topographies

25 people attended and learned the basic of machine learning and deep learning. The workshop concluded with a broad panel discussion on the application of machine learning to the X-Earth center research areas and a focused discussion of a set of X-Earth-centric problems to engage as part of future collaboration.

Dr. Alronso Gastelum Strozzi	Dr. Trevor Gee	Dr. Patrice Delmas

Assoc. Prof. Toshifumi Mukunoki－Organizer	Audience

69th IROAST Seminar