Titlebook: Artificial Intelligence and Soft Computing; 19th International C Leszek Rutkowski,Rafa? Scherer,Jacek M. Zurada Conference proceedings 2020

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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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https://doi.org/10.1007/978-3-031-45312-0works. The proposed strategy is to limit the modification of the weights of the networks entering a randomly selected set of neurons (activation function). Randomizing a fragment of the network whose parameters are modified is carried out in parallel with the selection of a mini-batch based on which

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Fundamental Theories of Physicsion. In this paper a new modification of the conjugate gradient algorithm is presented. The proposed solution speeds up the directional minimization, which result in a significant reduction of the calculation time. This modification of the CG algorithm was tested on selected examples. The performanc

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Fundamental Theories of Physicsf spam, detection of phishing attempts or for detection of fake messages. One of the areas where document classification is of growing importance is automatic assessment of civic, legal and government documents. Using automated classification, a governmental institution might scan all its incoming c

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https://doi.org/10.1007/978-1-4615-1331-5e of RVFL is fast training without backpropagation. This is because the weights and biases of hidden nodes are selected randomly and stay untrained. Recently, alternative architectures with randomized learning are developed which differ from RVFL in that they have no direct links and a bias term in

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https://doi.org/10.1007/978-1-4615-1331-5ically and resource-wise) services in the network so that no of the clients will be victimized and all of them will receive the best possible time of response. Also - there must be a balance not to instantiate a service on every possible machine - which would take too many resources. The task which

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Systems Science in Retrospect and Prospectrecognition and image classification than classic machine learning approach. Among the most used methods in DL, CNNs are for a special interest. In this work, we have developed an automatic classifier that permits to classify a large number of fashion clothing articles based on ML and DL approaches.

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