… in Germany cooperated with the US in computational neuroscience[8]. Japan also attaches …
’s latest research progress using deep learning intelligent technology in SAR ATR and …

… communication technology, machine learning and clinical … has brought great influence
on neuroscience. This study also … characteristics of the neurobiology of suicidality and real-world …

… A new trend in machine learning is currently emerging and is known as … SNN computational
framework called NeuCube departs significantly from the classical neuro-computation and …

… of depression with machine learning algorithm. Among them, it … is an important branch of
neuroscience. In the previous studies… properties, and use machine learning method to diagnose …

… neuroscience provides a promising framework for addressing this complexity with an
interdisciplinary paradigm by integrating neuroscience, … developmental population neuroscience …

: 为提高转化型和稳定型轻度认知障碍(mild cognitive impairment, MCI) 的分类精度, 利用阿尔
茨海默病样本和正常对照组样本学习投影矩阵, 使用监督图正则化项优化样本的局部近邻关系, …

… such as artificial intelligence, machine learning, image processing, and neurobiology. In this
thesis, we discuss three different applications combined with machine learning and pattern …

… This paper proposes a new framework that synergistically combines state-space modeling
with deep learning techniques to enable individualized disease prediction and to identify …

… [Objective] Based on the cross-modal deep learning method, this paper analyzes consumers’
sentiments in travel reviews and identifies their sarcastic expression. [Methods] First, we …