Extricate 发表于 2025-3-23 12:57:17

Lobar Ultrasound of the Breast,quence, HAR has been considered as a potential technology for e-health systems. Here, we propose a machine learning based HAR classifier. We also provide a full experimental description that contains the HAR wearable devices setup and a public domain dataset comprising 165,633 samples. We consider 5

Parallel 发表于 2025-3-23 13:57:12

https://doi.org/10.1007/978-3-319-96947-3es in many time series mining algorithms. Several solutions to pattern discovery have been proposed so far. However, all solutions assume centralized dataset. With increasingly development of network technology distributed data analysis has become popular, raising issues like scalability and cost mi

Introduction 发表于 2025-3-23 20:35:09

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反馈 发表于 2025-3-23 23:55:03

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强行引入 发表于 2025-3-24 06:16:34

Adnan Aydiner,Abdullah Igci,Atilla Soranvertices, these vertices common neighbors may play different roles depending on if they belong or not to the same cluster. Based on that, we propose a new measure (WIC) for link prediction between a pair of vertices considering the sets of their intra-cluster or within-cluster (W) and between-cluste

愚蠢人 发表于 2025-3-24 09:06:20

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SIT 发表于 2025-3-24 13:36:46

Surgical Approach in Invasive Breast Cancerrom textual data. However, currently available methods have some limitations to perform the incremental learning phase. In particular, when the initial topic hierarchy is not suitable for modeling the data, new documents are inserted into inappropriate topics and this error gets propagated into futu

断断续续 发表于 2025-3-24 17:35:00

https://doi.org/10.1007/978-3-642-83675-6 given object in a set of images with different backgrounds. This method is composed by three main modules: a visual attention model that is quite robust against affine transformations; a color-based schematic representation of visual information; and a genetic algorithm that optimizes several param

和蔼 发表于 2025-3-24 22:39:14

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SLUMP 发表于 2025-3-24 23:55:14

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查看完整版本: Titlebook: Advances in Artificial Intelligence - SBIA 2012; 21st Brazilian Sympo Leliane N. Barros,Marcelo Finger,Marcos Castilho Conference proceedin