Towards Spatially-Lucid AI Classification in Non-Euclidean Space: An Application for MxIF Oncology Data

no code implementations • 22 Feb 2024 • Majid Farhadloo, Arun Sharma, Jayant Gupta, Alexey Leontovich, Svetomir N. Markovic, Shashi Shekhar

Given multi-category point sets from different place-types, our goal is to develop a spatially-lucid classifier that can distinguish between two classes based on the arrangements of their points.

Domain Adaptation

SAMCNet for Spatial-configuration-based Classification: A Summary of Results

no code implementations • 22 Dec 2021 • Majid Farhadloo, Carl Molnar, Gaoxiang Luo, Yan Li, Shashi Shekhar, Rachel L. Maus, Svetomir N. Markovic, Raymond Moore, Alexey Leontovich

This problem is challenging due to an exponential number of category subsets which may vary in the strength of spatial interactions.

Representation Learning