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1
Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases
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Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases

Journal of pathology informatics, 2016-01, Vol.7 (1), p.29-29, Article 29 [Peer Reviewed Journal]

2016 The Authors ;Copyright Medknow Publications & Media Pvt Ltd 2016 ;Copyright: © 2016 Journal of Pathology Informatics 2016 ;ISSN: 2153-3539 ;ISSN: 2229-5089 ;EISSN: 2153-3539 ;DOI: 10.4103/2153-3539.186902 ;PMID: 27563488

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2
Using Deep Learning for Image-Based Plant Disease Detection
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Using Deep Learning for Image-Based Plant Disease Detection

Frontiers in plant science, 2016-09, Vol.7, p.1419-1419 [Peer Reviewed Journal]

Copyright © 2016 Mohanty, Hughes and Salathé. 2016 Mohanty, Hughes and Salathé ;ISSN: 1664-462X ;EISSN: 1664-462X ;DOI: 10.3389/fpls.2016.01419 ;PMID: 27713752

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3
A review of unsupervised feature learning and deep learning for time-series modeling
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A review of unsupervised feature learning and deep learning for time-series modeling

Pattern recognition letters, 2014-06, Vol.42 (1), p.11 [Peer Reviewed Journal]

ISSN: 0167-8655 ;ISSN: 1872-7344 ;EISSN: 1872-7344 ;DOI: 10.1016/j.patrec.2014.01.008

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4
Searching for exotic particles in high-energy physics with deep learning
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Searching for exotic particles in high-energy physics with deep learning

Nature communications, 2014-07, Vol.5 (1), p.4308-4308, Article 4308 [Peer Reviewed Journal]

Copyright Nature Publishing Group Jul 2014 ;ISSN: 2041-1723 ;EISSN: 2041-1723 ;DOI: 10.1038/ncomms5308 ;PMID: 24986233

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5
Mass detection in digital breast tomosynthesis: Deep convolutional neural network with transfer learning from mammography
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Mass detection in digital breast tomosynthesis: Deep convolutional neural network with transfer learning from mammography

Medical physics (Lancaster), 2016-12, Vol.43 (12), p.6654-6666 [Peer Reviewed Journal]

American Association of Physicists in Medicine ;2016 American Association of Physicists in Medicine ;2016 American Association of Physicists in Medicine. 2016 American Association of Physicists in Medicine ;ISSN: 0094-2405 ;EISSN: 2473-4209 ;DOI: 10.1118/1.4967345 ;PMID: 27908154 ;CODEN: MPHYA6

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6
Urinary bladder segmentation in CT urography using deep-learning convolutional neural network and level sets
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Urinary bladder segmentation in CT urography using deep-learning convolutional neural network and level sets

Medical physics (Lancaster), 2016-04, Vol.43 (4), p.1882-1896 [Peer Reviewed Journal]

American Association of Physicists in Medicine ;2016 American Association of Physicists in Medicine ;Copyright © 2016 American Association of Physicists in Medicine 2016 American Association of Physicists in Medicine ;ISSN: 0094-2405 ;EISSN: 2473-4209 ;DOI: 10.1118/1.4944498 ;PMID: 27036584 ;CODEN: MPHYA6

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7
Engineering Education and the Development of Expertise
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Article
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Engineering Education and the Development of Expertise

Journal of engineering education (Washington, D.C.), 2011-01, Vol.100 (1), p.123-150 [Peer Reviewed Journal]

2011 American Society for Engineering Education ;ISSN: 1069-4730 ;EISSN: 2168-9830 ;DOI: 10.1002/j.2168-9830.2011.tb00006.x ;CODEN: JEEDEQ

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8
ModDrop: adaptive multi-modal gesture recognition
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ModDrop: adaptive multi-modal gesture recognition

IEEE transactions on pattern analysis and machine intelligence, 2016-08 [Peer Reviewed Journal]

Distributed under a Creative Commons Attribution 4.0 International License ;ISSN: 0162-8828 ;EISSN: 1939-3539 ;DOI: 10.1109/TPAMI.2015.2461544

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9
Improved Automated Detection of Diabetic Retinopathy on a Publicly Available Dataset Through Integration of Deep Learning
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Improved Automated Detection of Diabetic Retinopathy on a Publicly Available Dataset Through Integration of Deep Learning

Investigative ophthalmology & visual science, 2016-10, Vol.57 (13), p.5200-5206 [Peer Reviewed Journal]

ISSN: 1552-5783 ;EISSN: 1552-5783 ;DOI: 10.1167/iovs.16-19964 ;PMID: 27701631

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10
Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition
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Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition

Sensors (Basel, Switzerland), 2016-01, Vol.16 (1), p.115 [Peer Reviewed Journal]

2016 by the authors; licensee MDPI, Basel, Switzerland. 2016 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s16010115 ;PMID: 26797612

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11
Reading Text in the Wild with Convolutional Neural Networks
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Reading Text in the Wild with Convolutional Neural Networks

International journal of computer vision, 2016-01, Vol.116 (1), p.1-20 [Peer Reviewed Journal]

Springer Science+Business Media New York 2015 ;COPYRIGHT 2016 Springer ;Springer Science+Business Media New York 2016 ;ISSN: 0920-5691 ;EISSN: 1573-1405 ;DOI: 10.1007/s11263-015-0823-z

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12
Deep learning for computational biology
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Deep learning for computational biology

Molecular systems biology, 2016-07, Vol.12 (7), p.878-n/a [Peer Reviewed Journal]

2016 The Authors. Published under the terms of the CC BY 4.0 license ;2016 The Authors. Published under the terms of the CC BY 4.0 license. ;2016 EMBO ;2016. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1744-4292 ;EISSN: 1744-4292 ;DOI: 10.15252/msb.20156651 ;PMID: 27474269

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13
Deep Neural Networks Reveal a Gradient in the Complexity of Neural Representations across the Ventral Stream
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Deep Neural Networks Reveal a Gradient in the Complexity of Neural Representations across the Ventral Stream

The Journal of neuroscience, 2015-07, Vol.35 (27), p.10005-10014 [Peer Reviewed Journal]

Copyright © 2015 the authors 0270-6474/15/3510005-10$15.00/0. ;Copyright © 2015 the authors 0270-6474/15/3510005-10$15.00/0 2015 ;ISSN: 0270-6474 ;EISSN: 1529-2401 ;DOI: 10.1523/JNEUROSCI.5023-14.2015 ;PMID: 26157000

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14
Learning Hierarchical Features for Scene Labeling
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Article
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Learning Hierarchical Features for Scene Labeling

IEEE transactions on pattern analysis and machine intelligence, 2013-08, Vol.35 (8), p.1915-1929 [Peer Reviewed Journal]

Distributed under a Creative Commons Attribution 4.0 International License ;ISSN: 0162-8828 ;EISSN: 1939-3539 ;DOI: 10.1109/TPAMI.2012.231

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15
Deep Dynamic Neural Networks for Multimodal Gesture Segmentation and Recognition
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Article
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Deep Dynamic Neural Networks for Multimodal Gesture Segmentation and Recognition

IEEE transactions on pattern analysis and machine intelligence, 2016-08, Vol.38 (8), p.1583-1597 [Peer Reviewed Journal]

ISSN: 0162-8828 ;EISSN: 1939-3539 ;DOI: 10.1109/TPAMI.2016.2537340 ;PMID: 26955020 ;CODEN: ITPIDJ

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16
Machine Learning in Genomic Medicine: A Review of Computational Problems and Data Sets
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Article
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Machine Learning in Genomic Medicine: A Review of Computational Problems and Data Sets

Proceedings of the IEEE, 2016-01, Vol.104 (1), p.176-197 [Peer Reviewed Journal]

ISSN: 0018-9219 ;EISSN: 1558-2256 ;DOI: 10.1109/JPROC.2015.2494198 ;CODEN: IEEPAD

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17
Molecular graph convolutions: moving beyond fingerprints
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Article
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Molecular graph convolutions: moving beyond fingerprints

Journal of computer-aided molecular design, 2016-08, Vol.30 (8), p.595-608 [Peer Reviewed Journal]

Springer International Publishing Switzerland 2016 ;ISSN: 0920-654X ;EISSN: 1573-4951 ;DOI: 10.1007/s10822-016-9938-8 ;PMID: 27558503

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18
Training Deep Spiking Neural Networks Using Backpropagation
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Training Deep Spiking Neural Networks Using Backpropagation

Frontiers in neuroscience, 2016-11, Vol.10, p.508-508 [Peer Reviewed Journal]

2016. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;Copyright © 2016 Lee, Delbruck and Pfeiffer. 2016 Lee, Delbruck and Pfeiffer ;ISSN: 1662-4548 ;ISSN: 1662-453X ;EISSN: 1662-453X ;DOI: 10.3389/fnins.2016.00508 ;PMID: 27877107

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19
A Deep Learning Approach for Network Intrusion Detection System
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A Deep Learning Approach for Network Intrusion Detection System

EAI endorsed transactions on security and safety, 2016-12, Vol.3 (9), p.21-6 [Peer Reviewed Journal]

2016. This work is licensed under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;EISSN: 2032-9393 ;DOI: 10.4108/eai.3-12-2015.2262516

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20
Deep convolutional neural networks for multi-modality isointense infant brain image segmentation
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Deep convolutional neural networks for multi-modality isointense infant brain image segmentation

NeuroImage (Orlando, Fla.), 2015-03, Vol.108, p.214-224 [Peer Reviewed Journal]

2014 Elsevier Inc. ;Copyright © 2014 Elsevier Inc. All rights reserved. ;Copyright Elsevier Limited Mar 1, 2015 ;2014 Elsevier Inc. All rights reserved. 2014 ;ISSN: 1053-8119 ;EISSN: 1095-9572 ;DOI: 10.1016/j.neuroimage.2014.12.061 ;PMID: 25562829

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