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Found 3 papers, 2 papers with code
Towards Effective Multi-Label Recognition Attacks via Knowledge Graph Consistency
We show that the naive extensions of multi-class attacks to the multi-label setting lead to violating label relationships, modeled by a knowledge graph, and can be detected using a consistency verification scheme.
Exploring Intensity Invariance in Deep Neural Networks for Brain Image Registration
We find a performance degradation of these models when brain image pairs with different intensity distribution are presented even with similar structures.
Rethinking Table Recognition using Graph Neural Networks
In this paper, we propose an architecture based on graph networks as a better alternative to standard neural networks for table recognition.
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