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Items: 1 to 20 of 88

1.

Using a machine learning approach to determine the space group of a structure from the atomic pair distribution function.

Liu CH, Tao Y, Hsu D, Du Q, Billinge SJL.

Acta Crystallogr A Found Adv. 2019 Jul 1;75(Pt 4):633-643. doi: 10.1107/S2053273319005606. Epub 2019 Jun 26.

PMID:
31264647
2.

Classification of crystal structure using a convolutional neural network.

Park WB, Chung J, Jung J, Sohn K, Singh SP, Pyo M, Shin N, Sohn KS.

IUCrJ. 2017 Jun 13;4(Pt 4):486-494. doi: 10.1107/S205225251700714X. eCollection 2017 Jul 1.

3.

Geometric Convolutional Neural Network for Analyzing Surface-Based Neuroimaging Data.

Seong SB, Pae C, Park HJ.

Front Neuroinform. 2018 Jul 6;12:42. doi: 10.3389/fninf.2018.00042. eCollection 2018.

4.

Learning transferable features in deep convolutional neural networks for diagnosing unseen machine conditions.

Han T, Liu C, Yang W, Jiang D.

ISA Trans. 2019 Mar 25. pii: S0019-0578(19)30136-3. doi: 10.1016/j.isatra.2019.03.017. [Epub ahead of print]

PMID:
30935654
5.

CNN-BLPred: a Convolutional neural network based predictor for β-Lactamases (BL) and their classes.

White C, Ismail HD, Saigo H, Kc DB.

BMC Bioinformatics. 2017 Dec 28;18(Suppl 16):577. doi: 10.1186/s12859-017-1972-6.

6.

Joint multiple fully connected convolutional neural network with extreme learning machine for hepatocellular carcinoma nuclei grading.

Li S, Jiang H, Pang W.

Comput Biol Med. 2017 May 1;84:156-167. doi: 10.1016/j.compbiomed.2017.03.017. Epub 2017 Mar 22.

PMID:
28365546
7.

Bi-stream CNN Down Syndrome screening model based on genotyping array.

Feng B, Hoskins W, Zhang Y, Meng Z, Samuels DC, Wang J, Xia R, Liu C, Tang J, Guo Y.

BMC Med Genomics. 2018 Nov 20;11(Suppl 5):105. doi: 10.1186/s12920-018-0416-0.

8.

Fast learning method for convolutional neural networks using extreme learning machine and its application to lane detection.

Kim J, Kim J, Jang GJ, Lee M.

Neural Netw. 2017 Mar;87:109-121. doi: 10.1016/j.neunet.2016.12.002. Epub 2016 Dec 10.

PMID:
28110106
9.

[Research on convolutional neural network and its application on medical image].

Liang M, Zhou T, Zhang F, Yang J, Xia Y.

Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2018 Dec 25;35(6):977-985. doi: 10.7507/1001-5515.201710060. Review. Chinese.

PMID:
30583326
10.

Analyzing modal power in multi-mode waveguide via machine learning.

Liu A, Lin T, Han H, Zhang X, Chen Z, Gan F, Lv H, Liu X.

Opt Express. 2018 Aug 20;26(17):22100-22109. doi: 10.1364/OE.26.022100.

PMID:
30130908
11.

Deformable Image Registration based on Similarity-Steered CNN Regression.

Cao X, Yang J, Zhang J, Nie D, Kim MJ, Wang Q, Shen D.

Med Image Comput Comput Assist Interv. 2017 Sep;10433:300-308. doi: 10.1007/978-3-319-66182-7_35. Epub 2017 Sep 4.

12.

MANTIS: Model-Augmented Neural neTwork with Incoherent k-space Sampling for efficient MR parameter mapping.

Liu F, Feng L, Kijowski R.

Magn Reson Med. 2019 Jul;82(1):174-188. doi: 10.1002/mrm.27707. Epub 2019 Mar 12.

PMID:
30860285
13.

Classification of G-protein coupled receptors based on a rich generation of convolutional neural network, N-gram transformation and multiple sequence alignments.

Li M, Ling C, Xu Q, Gao J.

Amino Acids. 2018 Feb;50(2):255-266. doi: 10.1007/s00726-017-2512-4. Epub 2017 Nov 18.

PMID:
29151135
14.

Pulmonary nodule classification in lung cancer screening with three-dimensional convolutional neural networks.

Liu S, Xie Y, Jirapatnakul A, Reeves AP.

J Med Imaging (Bellingham). 2017 Oct;4(4):041308. doi: 10.1117/1.JMI.4.4.041308. Epub 2017 Nov 14.

15.

Evolution of Deep Convolutional Neural Networks Using Cartesian Genetic Programming.

Suganuma M, Kobayashi M, Shirakawa S, Nagao T.

Evol Comput. 2019 Mar 22:1-23. doi: 10.1162/evco_a_00253. [Epub ahead of print]

PMID:
30900927
16.

Segmentation of lung parenchyma in CT images using CNN trained with the clustering algorithm generated dataset.

Xu M, Qi S, Yue Y, Teng Y, Xu L, Yao Y, Qian W.

Biomed Eng Online. 2019 Jan 3;18(1):2. doi: 10.1186/s12938-018-0619-9.

17.

Deep learning-based classification with improved time resolution for physical activities of children.

Jang Y, Kim S, Kim K, Lee D.

PeerJ. 2018 Oct 19;6:e5764. doi: 10.7717/peerj.5764. eCollection 2018.

18.

Bearing Fault Diagnosis with a Feature Fusion Method Based on an Ensemble Convolutional Neural Network and Deep Neural Network.

Li H, Huang J, Ji S.

Sensors (Basel). 2019 Apr 30;19(9). pii: E2034. doi: 10.3390/s19092034.

19.

Voiceprint Identification for Limited Dataset Using the Deep Migration Hybrid Model Based on Transfer Learning.

Sun C, Yang Y, Wen C, Xie K, Wen F.

Sensors (Basel). 2018 Jul 23;18(7). pii: E2399. doi: 10.3390/s18072399.

20.

A Novel Deep Learning Method for Intelligent Fault Diagnosis of Rotating Machinery Based on Improved CNN-SVM and Multichannel Data Fusion.

Gong W, Chen H, Zhang Z, Zhang M, Wang R, Guan C, Wang Q.

Sensors (Basel). 2019 Apr 9;19(7). pii: E1693. doi: 10.3390/s19071693.

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