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

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書目名稱Artificial Intelligence and Soft Computing影響因子(影響力)




書目名稱Artificial Intelligence and Soft Computing影響因子(影響力)學(xué)科排名




書目名稱Artificial Intelligence and Soft Computing網(wǎng)絡(luò)公開度




書目名稱Artificial Intelligence and Soft Computing網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Artificial Intelligence and Soft Computing被引頻次




書目名稱Artificial Intelligence and Soft Computing被引頻次學(xué)科排名




書目名稱Artificial Intelligence and Soft Computing年度引用




書目名稱Artificial Intelligence and Soft Computing年度引用學(xué)科排名




書目名稱Artificial Intelligence and Soft Computing讀者反饋




書目名稱Artificial Intelligence and Soft Computing讀者反饋學(xué)科排名

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盤旋

現(xiàn)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.

熔巖

莊嚴(yán)

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