全部文献期刊学位论文会议报纸专利标准年鉴图书|学者科研项目
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作者:Mehmet Eren Ahsen , Todd P. Boren , Nitin K. Singh ...
来源:[J].BMC Genomics(IF 4.397), 2017, Vol.18 (3)Springer
摘要:Metastasis via pelvic and/or para-aortic lymph nodes is a major risk factor for endometrial cancer. Lymph-node resection ameliorates risk but is associated with significant co-morbidities. Incidence in patients with stage I disease is 4–22% but no mechanism exists to accurat...
作者:Chuan Zhao , Zhipeng Feng , Xiukun Wei ...
来源:[J].Expert Systems With Applications(IF 1.854), 2018, Vol.108, pp.233-245Elsevier
摘要:... In order to overcome this difficulty, a sparse classification framework based on dictionary learning is proposed. It operates directly on raw signals and is free from steps involved in conventional pattern identification such as feature design which requires prior expertise. ...
作者:Sara Ahmadi , Seyed Mohammad Ahadi , Bert Cranen ...
来源:[J].EURASIP Journal on Audio, Speech, and Music Processing(IF 0.63), 2014, Vol.2014 (1), pp.1-20Springer
摘要:... In this paper we use the raw output of a modulation spectrum analyser in combination with sparse coding as a means for obtaining state posterior probabilities. The modulation spectrum analyser uses 15 gammatone filters. The Hilbert envelope of the output of these filters is t...
作者:Yang Sun , Jort F. Gemmeke , Bert Cranen ...
来源:[J].Speech Communication(IF 1.283), 2014, Vol.56, pp.49-62Elsevier
摘要:... a second estimate is obtained from a non-parametric Sparse Classification (SC) system. During training the parameters pertaining to the input streams can be optimized independently, but also jointly, provided that all streams represent true probability functions. During decod...
作者:Nan Wang , Yiming Xue , Qiang Lin ...
来源:[J].Multimedia Tools and Applications(IF 1.014), 2019, Vol.78 (11), pp.15455-15481Springer
摘要:... The newly proposed multi-view weighted hinge loss penalty not only has the ability to select more discriminative features for classification, but also can make the involved optimization problem be decomposed into several small scale subproblems, which can be easily solved by ...
作者:G. Krishna Vinay , S. M. Haque , R. Venkatesh Babu ...
来源:[J].Signal, Image and Video Processing(IF 0.409), 2016, Vol.10 (3), pp.585-592Springer
摘要:... Here, we address this problem in sparse representation framework with an overcomplete scale-embedded dictionary. Histogram of oriented gradient features extracted from the candidate image patches are sparsely represented by the dictionary that contain positive bases along wit...
作者:Mingxia Liu , Jun Zhang , Xiaochun Guo ...
来源:[J].Neurocomputing(IF 1.634), 2017, Vol.237, pp.185-192Elsevier
摘要:... However, most of existing l 1 -norm based sparse feature selection methods ignore the structure information of data or only consider the pairwise relationships among samples. In this paper, we propose a hypergraph regularized sparse feature learning method, where the high-ord...
作者:Gang Tang , Qin Yang , Hua-Qing Wang ...
来源:[J].Mechatronics(IF 1.3), 2015, Vol.31, pp.60-67Elsevier
摘要:... Fault identification and classifications for rotating machinery are investigated in this study utilizing expanded monitoring data. A representation classification strategy for rotating machinery faults is developed based on a newly developed compressive sensing theory focusin...
作者:Gang Tang , Qin Yang , Hua-Qing Wang ...
来源:[J].Mechatronics(IF 1.3), 2015, Vol.31, pp.60-67Elsevier
摘要:... Fault identification and classifications for rotating machinery are investigated in this study utilizing expanded monitoring data. A representation classification strategy for rotating machinery faults is developed based on a newly developed compressive sensing theory focusin...
作者:Mingxia Liu , Jun Zhang , Xiaochun Guo ...
来源:[J].Neurocomputing(IF 1.634), 2016Elsevier
摘要:... However, most of existing l 1 -norm based sparse feature selection methods ignore the structure information of data or only consider the pairwise relationships among samples. In this paper, we propose a hypergraph regularized sparse feature learning method, where the high-ord...

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