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Titlebook: Artificial Intelligence in Neuroscience: Affective Analysis and Health Applications; 9th International Wo José Manuel Ferrández Vicente,Jos

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發(fā)表于 2025-3-26 23:23:43 | 只看該作者
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發(fā)表于 2025-3-27 01:41:51 | 只看該作者
Towards Mixed Mode Biomarkers: Combining Structural and?Functional Information by?Deep Learningion of an image by combining a source image to another that determines the . of the final result. In the field of neuroimaging, different modalities are frequently available, providing structural or functional information. Those modalities are usually analyzed separately, although it is possible to
33#
發(fā)表于 2025-3-27 09:13:32 | 只看該作者
Modelling the?Progression of?the?Symptoms of?Parkinsons Disease Using a?Nonlinear Decomposition of?1ion in the neurotransmitter dopamine, which is essential in the control of movement. While the diagnosis of PD is mainly clinical, new markers are being used with high accuracy in the later stages of the disease, where symptoms are clear. However, the early stages of the disease, when symptoms start
34#
發(fā)表于 2025-3-27 13:27:19 | 只看該作者
Capacity Estimation from?Environmental Audio Signals Using Deep Learningntee a minimal safety distance between people is also essential for health reasons, as in the current COVID-19 pandemic. Already existing systems for automatic crowd counting are mostly based on image or video data, and some of them, using deep learning architectures. In this paper, we study the via
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發(fā)表于 2025-3-27 17:21:29 | 只看該作者
36#
發(fā)表于 2025-3-27 20:20:27 | 只看該作者
RDNet: ResNet-18 with?Dropout for?Blood Cell Classificationect the hematopoietic system with abnormal blood changes, characterized by anemia, bleeding, and fever. It is helpful for doctors to diagnose blood diseases by classifying blood cells. However, doctors take a lot of time and energy to classify blood cells. The classification process is easily distur
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發(fā)表于 2025-3-28 00:21:01 | 只看該作者
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發(fā)表于 2025-3-28 03:22:19 | 只看該作者
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發(fā)表于 2025-3-28 08:39:44 | 只看該作者
40#
發(fā)表于 2025-3-28 13:12:39 | 只看該作者
Evaluating Intensity Concentrations During the?Spatial Normalization of?Functional Images for?Parkinum using a linear and/or a non-linear registration to a reference template. For that, the deformation has been indirectly measured studying the changes in the intensity values in two different scenarios when, during the interpolation stage, the amount or the concentrations of intensity values are pr
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