| 000 | 02827nlm2a2200385 4500 | ||
|---|---|---|---|
| 001 | 657793 | ||
| 005 | 20231030041526.0 | ||
| 035 | _a(RuTPU)RU\TPU\network\24554 | ||
| 090 | _a657793 | ||
| 100 | _a20180321a2017 k y0engy50 ba | ||
| 101 | 0 | _aeng | |
| 102 | _aGB | ||
| 105 | _ay z 100zy | ||
| 135 | _adrcn ---uucaa | ||
| 181 | 0 | _ai | |
| 182 | 0 | _ab | |
| 200 | 1 |
_aDeep Learning for ECG Classification _fB. I. Pyakullya, N. E. Kazachenko, N. E. Mikhaylovskiy |
|
| 203 |
_aText _celectronic |
||
| 300 | _aTitle screen | ||
| 320 | _a[References: 11 tit.] | ||
| 330 | _aThe importance of ECG classification is very high now due to many current medical applications where this problem can be stated. Currently, there are many machine learning (ML) solutions which can be used for analyzing and classifying ECG data. However, the main disadvantages of these ML results is use of heuristic hand-crafted or engineered features with shallow feature learning architectures. The problem relies in the possibility not to find most appropriate features which will give high classification accuracy in this ECG problem. One of the proposing solution is to use deep learning architectures where first layers of convolutional neurons behave as feature extractors and in the end some fully-connected (FCN) layers are used for making final decision about ECG classes. In this work the deep learning architecture with 1D convolutional layers and FCN layers for ECG classification is presented and some classification results are showed. | ||
| 461 | 0 |
_0(RuTPU)RU\TPU\network\3526 _tJournal of Physics: Conference Series |
|
| 463 |
_tVol. 913 : BigData Conference (Formerly International Conference on Big Data and Its Applications) _oInternational Conference, 15 September 2017, Moscow, Russian Federation _v[012004, 6 p.] _d2017 |
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| 610 | 1 | _aэлектронный ресурс | |
| 610 | 1 | _aтруды учёных ТПУ | |
| 610 | 1 | _aЭКГ | |
| 610 | 1 | _aобучение | |
| 610 | 1 | _aклассификации | |
| 700 | 1 |
_aPyakullya _bB. I. _cspecialist in the field of informatics and computer technology _cdesign engineer of Tomsk Polytechnic University _f1990- _gBoris Ivanovich _2stltpush _3(RuTPU)RU\TPU\pers\34170 |
|
| 701 | 1 |
_aKazachenko _bN. E. _gNataljya Evgenjevna |
|
| 701 | 1 |
_aMikhaylovskiy _bN. E. _gNikolay Ernestovich |
|
| 712 | 0 | 2 |
_aНациональный исследовательский Томский политехнический университет _bИнженерная школа информационных технологий и робототехники _bОтделение автоматизации и робототехники (ОАР) _h7952 _2stltpush _3(RuTPU)RU\TPU\col\23553 |
| 801 | 2 |
_aRU _b63413507 _c20180321 _gRCR |
|
| 856 | 4 | _uhttps://doi.org/10.1088/1742-6596/913/1/012004 | |
| 942 | _cCF | ||