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Xin Tian and Yuan Meng
Multi-relational graph neural networks (GNNs) have found widespread application in tasks involving enhancing knowledge representation and knowledge graph (KG) reasoning. However, existing multi-relational GNNs still face limitations in modeling the excha...
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Woonghee Lee and Younghoon Kim
This study introduces a deep-learning-based framework for detecting adversarial attacks in CT image segmentation within medical imaging. The proposed methodology includes analyzing features from various layers, particularly focusing on the first layer, a...
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Jinghua Li, Yidong Chen, Lei Zhou, Ruipu Dong, Wenhao Yin, Wenhao Huang and Fan Zhang
In the context of increasingly competitive shipbuilding, the flexible multi-level picking system, composed of high-rise shelves, Automated Guided Vehicles (AGVs), and picking stations, has been of gradual interest because of its advantages in operation e...
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Han Zhang, Yadong Wu, Weihan Zhang and Yuling Zhang
The precise ascertainment of stellar ages is pivotal for astrophysical research into stellar characteristics and galactic dynamics. To address the prevalent challenges of suboptimal accuracy in stellar age determination and limited proficiency in apprehe...
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Gleice Kelly Barbosa Souza, Samara Oliveira Silva Santos, André Luiz Carvalho Ottoni, Marcos Santos Oliveira, Daniela Carine Ramires Oliveira and Erivelton Geraldo Nepomuceno
Reinforcement learning is an important technique in various fields, particularly in automated machine learning for reinforcement learning (AutoRL). The integration of transfer learning (TL) with AutoRL in combinatorial optimization is an area that requir...
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