拥挤前 发表于 2025-3-28 18:07:38
Activity Recognition for Traditional Dances Using Dimensionality Reductiona general dimensionality reduction framework. Experiments on a traditional dance recognition dataset are conducted and the advantage of using dimensionality reduction before classification is highlighted.Forage饲料 发表于 2025-3-28 19:00:53
http://reply.papertrans.cn/17/1626/162577/162577_42.pngascetic 发表于 2025-3-28 23:07:38
http://reply.papertrans.cn/17/1626/162577/162577_43.png小步走路 发表于 2025-3-29 05:05:09
Artificial Intelligence: Methods and Applications978-3-319-07064-3Series ISSN 0302-9743 Series E-ISSN 1611-3349nominal 发表于 2025-3-29 08:33:20
Fehlermeldeverhalten in der Pflege propose an algorithm for the propagation of belief functions in the singly-connected directed evidential networks, when each node is associated with one conditional belief function distribution specified given all its parents.原始 发表于 2025-3-29 13:40:25
Zyklische Codes und CRC-Verfahren,or variable selection and classifier) and tune their hyper-parameters (e.g., K in K-NN), also called ., and (b) provide an estimate of the performance of the final, reported model. Combining the two tasks is not trivial because when one selects the set of hyper-parameters that seem to provide the be600 发表于 2025-3-29 18:48:27
Eingangsbeispiele und Blockcodes,ess either from scratch with an empty rule base or from an initially trained fuzzy model. Importantly, pClass not only adopts the open structure concept, where an automatic knowledge building process can be cultivated during the training process, which is well-known as a main pillar to learn from stdisciplined 发表于 2025-3-29 23:48:36
http://reply.papertrans.cn/17/1626/162577/162577_48.pngPlatelet 发表于 2025-3-30 00:54:54
http://reply.papertrans.cn/17/1626/162577/162577_49.png手术刀 发表于 2025-3-30 04:30:17
Eingangsbeispiele und Blockcodes, Transfer learning comprises a suitable solution for reinforcement learning algorithms, which often require a considerable amount of training time, especially when dealing with complex tasks. This work proposes an autonomous method for transfer learning in reinforcement learning agents. The proposed