Fast Classification of Meat Spoilage Markers Using Nanostructured ZnO Thin Films and Unsupervised Feature Learning

Sensors ◽

10.3390/s130201578 ◽

2013 ◽

Vol 13 (2) ◽

pp. 1578-1592 ◽

Author(s):

Martin Längkvist ◽

Silvia Coradeschi ◽

Amy Loutfi ◽

John Rayappan

Keyword(s):

Feature Learning ◽

Zno Thin Films ◽

Unsupervised Feature Learning ◽

Meat Spoilage ◽

Fast Classification

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Detection and classification of transmission line faults based on unsupervised feature learning and convolutional sparse autoencoder

2017 IEEE Power & Energy Society General Meeting ◽

10.1109/pesgm.2017.8273992 ◽

2017 ◽

Author(s):

Kunjin Chen ◽

Jun Hu ◽

Jinliang He

Keyword(s):

Transmission Line ◽

Feature Learning ◽

Unsupervised Feature Learning ◽

Sparse Autoencoder

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Detection and Classification of Transmission Line Faults Based on Unsupervised Feature Learning and Convolutional Sparse Autoencoder

IEEE Transactions on Smart Grid ◽

10.1109/tsg.2016.2598881 ◽

2016 ◽

pp. 1-1 ◽

Author(s):

Kunjin Chen ◽

Jun Hu ◽

Jinliang He

Keyword(s):

Transmission Line ◽

Feature Learning ◽

Unsupervised Feature Learning ◽

Sparse Autoencoder

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Automatic Classification of Turner Syndrome Using Unsupervised Feature Learning

2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC) ◽

10.1109/smc42975.2020.9283194 ◽

2020 ◽

Author(s):

Lu Liu ◽

Jingchao Sun ◽

Jianqiang Li ◽

Yan Pei

Keyword(s):

Turner Syndrome ◽

Feature Learning ◽

Automatic Classification ◽

Unsupervised Feature Learning

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Unsupervised feature learning for scene classification of high resolution remote sensing image

2015 IEEE China Summit and International Conference on Signal and Information Processing (ChinaSIP) ◽

10.1109/chinasip.2015.7230392 ◽

2015 ◽

Author(s):

Min Fu ◽

Yuan Yuan ◽

Xiaoqiang Lu

Keyword(s):

Remote Sensing ◽

High Resolution ◽

Feature Learning ◽

Remote Sensing Image ◽

Unsupervised Feature Learning ◽

Scene Classification

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Classification of waveforms using unsupervised feature learning and artificial neural network

2015 IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) ◽

10.1109/iaeac.2015.7428545 ◽

2015 ◽

Author(s):

Bendong Zhao ◽

Shangfeng Chen ◽

Junliang Liu ◽

Huanzhang Lu

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Feature Learning ◽

Unsupervised Feature Learning ◽

Artificial Neural

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Automatic large-scale classification of bird sounds is strongly improved by unsupervised feature learning

PeerJ ◽

10.7717/peerj.488 ◽

2014 ◽

Vol 2 ◽

pp. e488 ◽

Author(s):

Dan Stowell ◽

Mark D. Plumbley

Keyword(s):

Large Scale ◽

Feature Learning ◽

Unsupervised Feature Learning ◽

Scale Classification

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Peer Review #1 of "Automatic large-scale classification of bird sounds is strongly improved by unsupervised feature learning (v0.1)"

10.7287/peerj.488v0.1/reviews/1 ◽

2014 ◽

Keyword(s):

Peer Review ◽

Large Scale ◽

Feature Learning ◽

Unsupervised Feature Learning ◽

Scale Classification

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Peer Review #2 of "Automatic large-scale classification of bird sounds is strongly improved by unsupervised feature learning (v0.2)"

10.7287/peerj.488v0.2/reviews/2 ◽

2014 ◽

Keyword(s):

Peer Review ◽

Large Scale ◽

Feature Learning ◽

Unsupervised Feature Learning ◽

Scale Classification

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Peer Review #2 of "Automatic large-scale classification of bird sounds is strongly improved by unsupervised feature learning (v0.1)"

10.7287/peerj.488v0.1/reviews/2 ◽

2014 ◽

Keyword(s):

Peer Review ◽

Large Scale ◽

Feature Learning ◽

Unsupervised Feature Learning ◽

Scale Classification

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Classification of Breast Tumor in Mammogram Images Using Unsupervised Feature Learning

American Journal of Applied Sciences ◽

10.3844/ajassp.2016.552.561 ◽

2016 ◽

Vol 13 (5) ◽

pp. 552-561

Author(s):

Aidarus M. Ibrahim ◽

Baharum Baharudin ◽

Abas Md Said ◽

P. N. Hashimah

Keyword(s):

Breast Tumor ◽

Feature Learning ◽

Unsupervised Feature Learning ◽

Mammogram Images

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