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physically interpretable residual strength prediction of corroded pipelines via symbolic Bayesian networks. [PDF]
Sci RepChen M, Zhang Y, Ye Y, Lu Y.
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Underlying Sources of Response-Response Contingency Learning. [PDF]
J CognRothermund K +3 more
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Evaluating deep learning models for pancreatic cancer diagnosis. [PDF]
Clin Exp MedLi D, He H, Hu J, Ding Y, Kong L, Hu A.
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Learning residual alternating automata
Information and Computation, 2017Residuality plays an essential role for learning finite automata. While residual deterministic and non-deterministic automata have been understood quite well, fundamental questions concerning alternating automata (AFA) remain open. Recently, Angluin, Eisenstat, and Fisman (2015) have initiated a systematic study of residual AFAs and ...
Berndt, Sebastian +3 more
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Residual Learning for Salient Object Detection
IEEE Transactions on Image Processing, 2020Recent deep learning based salient object detection methods improve the performance by introducing multi-scale strategies into fully convolutional neural networks (FCNs). The final result is obtained by integrating all the predictions at each scale.
Mengyang Feng, Huchuan Lu, Yizhou Yu
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Learning Residual Color for Novel View Synthesis
IEEE Transactions on Image Processing, 2022Scene Representation Networks (SRN) have been proven as a powerful tool for novel view synthesis in recent works. They learn a mapping function from the world coordinates of spatial points to radiance color and the scene's density using a fully connected network. However, scene texture contains complex high-frequency details in practice that is hard to
Lei Han +4 more
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