3 citations · 7 across the 6 of their papers we have counts for
6 papers
A Data Augmentation Method and the Embedding Mechanism for Detection and Classification of Pulmonary Nodules on Small Samples
Yang Liu, Yue-Jie Hou, Chen-Xin Qin +4
Detection of pulmonary nodules by CT is used for screening lung cancer in early stages.omputer aided diagnosis (CAD) based on deep-learning method can identify the suspected areas…
An Unsupervised Deep-Learning Method for Bone Age Assessment
Hao Zhu, Wan-Jing Nie, Yue-Jie Hou +3
The bone age, reflecting the degree of development of the bones, can be used to predict the adult height and detect endocrine diseases of children. Both examinations of radiologist…
Early Abnormal Detection of Sewage Pipe Network: Bagging of Various Abnormal Detection Algorithms
Zhen-Yu Zhang, Guo-Xiang Shao, Chun-Ming Qiu +3
Abnormalities of the sewage pipe network will affect the normal operation of the whole city. Therefore, it is important to detect the abnormalities early. This paper propose an ear…
Why Existing Machine Learning Methods Fails At Extracting the Information of Future Returns Out of Historical Sctock Prices : the Curve-Shape-Feature and Non-Curve-Shape-Feature Modes
Jia-Yao Yang, Hao Zhu, Yue-Jie Hou +2
The financial time series analysis is important access to touch the complex laws of financial markets. Among many goals of the financial time series analysis, one is to construct a…
An Unsupervised Deep-Learning Method for Fingerprint Classification: the CCAE Network and the Hybrid Clustering Strategy
Yue-Jie Hou, Zai-Xin Xie, Jian-Hu +2
The fingerprint classification is an important and effective method to quicken the process and improve the accuracy in the fingerprint matching process. Conventional supervised met…
Activation functions are not needed: the ratio net
Chi-Chun Zhou, Hai-Long Tu, Yue-Jie Hou +3
A deep neural network for classification tasks is essentially consist of two components: feature extractors and function approximators. They usually work as an integrated whole, ho…