… of life sciences, including neuroscience. A recent study traced … , and has been used to
implement deep learning.Likewise, … Machine learning and deep neural networks in thoracic and …

… 新型Neuro-SM 模型,在直流特性仿真中对比粗模型, 传统Neuro-SM 模型以及所提出的新型
Neuro-SM 模型 的仿真结果与误差,结果表明,所提出的新型NeuroSM 模型是可行的,比传统Neuro-…

… Our objective is to make it easier to port the applications from the neuroscientists’ community
to … DianNao: A small-footprint high-throughput accelerator for ubiquitous machinelearning. …

… Deep learning has made great breakthroughs in many research fields with the development
of machine learning. Most deep learning methods need a large number of labeled data for …

… of applications in preclinical neuroscience. In contrast to … performed LSFM-deep learning
quantitative volume analysis … analysis coupled with deep learning computational methods …

… The purpose of this article is to briefly introduce the diverse ideas from 2000 to 2010 in
cultural neuroscience and to trace some typical fMRI studies in this field. In 2007 , Chiao and …

… 摘要回顾了深度学习(deep learning,DL)技术在睡眠脑电检测上的应用. 以睡眠脑电过程中的
纺锤波检测问题为 例,探讨了睡眠脑电检测的各类方法,以及相较于传统信号处理算法,DL 算法在…

… 3 Evolving deep neuro network based employment framework … 4 Evolving deep neuro
network based learning framework for dynamical … 5 Architecture of deep neuro network for UAVi …

… 集合,類神經模糊系統(neuro-fuzzy system, NFS) … neuro-fuzzy intelligent approach using CFSs
for the applications of system modeling. The proposed approach integrates a complex neuro…

… of modern deep learning techniques. However, as deep learning networks grow deeper, …
Supervised Contrastive Parallel Learning (SCPL) is a novel approach that decouples BP by …