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Found 4 papers, 1 papers with code
TRR360D: A dataset for 360 degree rotated rectangular box table detection
To address the problem of scarcity and high annotation costs of rotated image table detection datasets, this paper proposes a method for building a rotated image table detection dataset.
Ranked #1 on
2D Object Detection
on TRR360D
Ensemble manifold based regularized multi-modal graph convolutional network for cognitive ability prediction
Methods: To take advantage of complementary information from multi-modal fMRI, we propose an interpretable multi-modal graph convolutional network (MGCN) model, incorporating the fMRI time series and the functional connectivity (FC) between each pair of brain regions.
Causal inference of brain connectivity from fMRI with $ψ$-Learning Incorporated Linear non-Gaussian Acyclic Model ($ψ$-LiNGAM)
A popular definition of FC is by statistical associations between measured brain regions.
Interpretable multimodal fusion networks reveal mechanisms of brain cognition
Moreover, the estimated activation maps are class-specific, and the captured cross-data associations are interest/label related, which further facilitates class-specific analysis and biological mechanism analysis.
