Titlebook: Artificial Intelligence and Soft Computing; 22nd International C Leszek Rutkowski,Rafał Scherer,Jacek M. Zurada Conference proceedings 2023

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书目名称Artificial Intelligence and Soft Computing影响因子(影响力)




书目名称Artificial Intelligence and Soft Computing影响因子(影响力)学科排名




书目名称Artificial Intelligence and Soft Computing网络公开度




书目名称Artificial Intelligence and Soft Computing网络公开度学科排名




书目名称Artificial Intelligence and Soft Computing被引频次




书目名称Artificial Intelligence and Soft Computing被引频次学科排名




书目名称Artificial Intelligence and Soft Computing年度引用




书目名称Artificial Intelligence and Soft Computing年度引用学科排名




书目名称Artificial Intelligence and Soft Computing读者反馈




书目名称Artificial Intelligence and Soft Computing读者反馈学科排名

ticlopidine

盘旋

现存

Michel E. Domsch,Sven H. A. Siemers that the proposed FH-K-SVCR model retains the advantages of a .-SVCR which achieves high classification performance in multi-classes classification task, and increases fault tolerance and robustness by using fuzzy set theory.

Parallel

Magnificent

https://doi.org/10.1007/978-3-658-11219-6xiliary pretrained domain classification model can be used to build robust, shared domain feature representations. Our model achieves a classification accuracy improvement in standard cross-domain sentiment classification tasks over the baseline model in most cases.

SHOCK

Karlheinz Lohs,Peter Elstner,Ursula Stephanod improves the resilience to adversarial attacks by achieving up to 17.1%, 22.8%, and 16.6% higher accuracy against BIM, FGSM, and PGD attacks, respectively, over ResNet-18 trained on the CIFAR-10 dataset.

BOGUS

Reinforcement Learning with Brain-Inspired Modulation Improves Adaptation to Environmental Changesgorithms in simple but highly-dynamic tasks. It also exhibits a “paradox of choice” effect that has been observed in humans. The new rule may encapsulate a core principle of biological intelligence; an important component of human-like learning and adaptation - with both its benefits and trade-offs.

熔岩

庄严

Learning Representations by Crystallized Back-Propagating Errors Since neural hierarchies are established because of the algorithm, ANN compartments start to function in terms of cognitive levels. This study shows the importance of dealing with ANN in hierarchies through backpropagation and brings in learning methods as novel ways of interacting with ANN. Practi