IEEE Geoscience and Remote Sensing Magazine - June 2023 - 97

Gemine Vivone
Ronny Hänsch
Claudio Persello
Dalton Lunga
Gülsen Taskin
Ujjwal VermaFrancescopaolo Sica
FIGURE 3. The Organizing Committee of the first IEEE GRSS IADF School on CV4EO.
conventional image processing techniques. CV algorithms
enable the automatic interpretation of large data, allowing
remote sensing to be used for a wide range of applications,
including environmental monitoring, land use/cover
mapping, and natural resource management. Thus, the
IADF TC aimed for prioritizing topics that integrate CV
into remote sensing data analysis. The first IADF school
focused on applying CV techniques to address modern remote
sensing challenges, consisting of a series of lectures
discussing current methods for analyzing satellite images.
The covered topics were image fusion, explainable
artificial intelligence (AI) for Earth science, big geo-data,
multisource image analysis, deep learning for spectral
unmixing, SAR image analysis, and learning with zero/
few labels. The technical program of the IADF school is
depicted in Figure 4.
During the first day of the school, the " Deep/Machine
Learning for Spectral Unmixing " lecture covered various topics
related to linear hyperspectral unmixing. These included
geometrical approaches, blind linear unmixing, and sparse
unmixing. Additionally, the course
delved into the utilization of autoencoders
and convolutional
networks for unmixing purposes.
The lecture was followed by
" Change Detection (TorchGeo), "
which elaborated on the utilization
of TorchGeo with PyTorch
for training change detection
models using satellite imagery.
On the second day of the school,
the " Learning with Zero/Few
Labels " lecture discussed recent
developments in machine learning
with limited label data in EO, including semisupervised
learning, weakly supervised learning, and self-supervised
learning. The subsequent " SAR Processing " lecture covered
various topics, including the analysis of SAR images with
different polarimetric channels, the geometry of SAR image
JUNE 2023 IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE
Srija Chakraborty
REMOTE SENSING GENERATES
VAST AMOUNTS OF
IMAGE DATA THAT CAN
BE DIFFICULT AND TIME
CONSUMING TO ANALYZE
USING CONVENTIONAL
IMAGE PROCESSING
TECHNIQUES.
97

IEEE Geoscience and Remote Sensing Magazine - June 2023

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