Titlebook: Neural Information Processing; 22nd International C Sabri Arik,Tingwen Huang,Qingshan Liu Conference proceedings 2015 Springer Internationa

返老還童

Deep Convolutional Neural Networks for Human Activity Recognition with Smartphone Sensors,local dependency characteristics. Moreover, activities tend to be hierarchical and translation invariant in nature. Consequently, convolutional neural networks (convnet) exploit these characteristics, which make it appropriate in dealing with time-series sensor data. In this paper, we propose an arc

Assault

Concentration Monitoring with High Accuracy but Low Cost EEG Device,rocessing in human brain. To understand the concentration process of humans, the underlying neural mechanism needs to be explored. EEG device is a promising device to understand underlying neural mechanism of various cognitive functions. In this paper, we propose an accurate concentration monitoring

Cosmopolitan

保留

有效

A Study to Investigate Different EEG Reference Choices in Diagnosing Major Depressive Disorder,iency during diagnosis of psychiatric conditions, e.g., major depressive disorder (MDD). In literature, various EEG references have been proposed, however, none of them is considered as gold-standard [.]. Therefore, this study aims to evaluate 3 EEG references including infinity reference (IR), aver

黑豹

記憶

Enhancing Performance of EEG-based Emotion Recognition Systems Using Feature Smoothing,that the correlation between EEG and emotion characteristics is not taken into account. There are the differences among EEG features, even with the same emotion state in adjacent time because EEG extracted features usually change dramatically, while emotion states vary gradually or smoothly. In addi

肌肉

蔓藤圖飾

Mining Top-k Minimal Redundancy Frequent Patterns over Uncertain Databases,al approaches have been proposed for mining high significance frequent itemsets over uncertain data, however, previous algorithms yield many redundant frequent itemsets and require to set an appropriate user specified threshold which is difficult for users. In this paper, we formally define the prob

jumble