resuscitation 发表于 2025-3-28 15:46:47
http://reply.papertrans.cn/20/1903/190256/190256_41.pngObstreperous 发表于 2025-3-28 22:30:43
Morgane Joly,Éric Renault,Fabian Rivièreconnectivity of human brains, investigating sex differences across male and female connectomes (brain-graphs) for the knowledge discovery problem “.”. One of our main findings discloses the statistical difference at the pars orbitalis of the connectome between sexes, which has been shown to function取之不竭 发表于 2025-3-29 01:52:01
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http://reply.papertrans.cn/20/1903/190256/190256_44.png拥挤前 发表于 2025-3-29 11:05:31
Machine Learning for Networkingrom measurements. This paper addresses the measurement design problem of selecting . feasible measurements such that the mutual information between the unknown image and measurements is maximized, where . is a given budget. To calculate the mutual information, we utilize correlations of adjacent funcoltish 发表于 2025-3-29 15:08:16
Afsane Zahmatkesh,Chung-Horng Lungedures usually generate high-dimensional data. This complicates statistical analysis and modeling, resulting in high computational complexity and typically more complicated models. This study uses the features extracted from Positron Emission Tomography imagery by 3D Stereotactic Surface Projection.MOT 发表于 2025-3-29 19:16:20
Lecture Notes in Computer Science extracting not only parts that are exactly the same but also similar parts having a few differences since time-series data of cerebral blood flow is reported to be affected by various factors, and real data may therefore differ from a model system. To confirm the effectiveness of the proposed algor揉杂 发表于 2025-3-29 20:21:54
https://doi.org/10.1007/978-1-4842-7032-5e obtaining the rational result in a . fashion is more important in many real-world problems. A typical example in medical/brain informatics is that big stream data and protraction of analysis time are causing a burden of medical doctors or patients and therefore the feature extraction in a real-tim牵连 发表于 2025-3-30 01:56:42
Oracle Machine Learning for SQL,s paper proposes an unsupervised multi-scale K-means (MSK-means) algorithm to distinguish epileptic EEG signals from normal EEGs. The random initialization of the K-means algorithm can lead to wrong clusters. Based on the characteristics of EEGs, the MSK-means algorithm initializes the coarse-scalehomeostasis 发表于 2025-3-30 04:32:31
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