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|a 10.1007/978-3-030-63836-8
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|a HCDD
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2 |
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|a ICONIP (Conference)
|n (27th :
|d 2020 :
|c Bangkok, Thailand)
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| 245 |
1 |
0 |
|a Neural information processing :
|b 27th International Conference, ICONIP 2020, Bangkok, Thailand, November 23-27, 2020, Proceedings.
|n Part III /
|c Haiqin Yang, Kitsuchart Pasupa, Andrew Chi-Sing Leung, James T. Kwok, Jonathan H. Chan, Irwin King (eds.).
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| 246 |
3 |
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|a ICONIP 2020
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| 260 |
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|a Cham :
|b Springer,
|c 2020.
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| 300 |
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|a 1 online resource (660 pages)
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| 336 |
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|a text
|b txt
|2 rdacontent
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|a computer
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|2 rdamedia
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|a online resource
|b cr
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| 347 |
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|a text file
|2 rdaft
|0 http://rdaregistry.info/termList/fileType/1002
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| 347 |
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|b PDF
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| 490 |
1 |
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|a Lecture Notes in Computer Science ;
|v 12534
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| 490 |
1 |
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|a LNCS sublibrary, SL 1, Theoretical computer science and general issues
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| 520 |
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|a The three-volume set of LNCS 12532, 12533, and 12534 constitutes the proceedings of the 27th International Conference on Neural Information Processing, ICONIP 2020, held in Bangkok, Thailand, in November 2020. Due to COVID-19 pandemic the conference was held virtually. The 187 full papers presented were carefully reviewed and selected from 618 submissions. The papers address the emerging topics of theoretical research, empirical studies, and applications of neural information processing techniques across different domains. The third volume, LNCS 12534, is organized in topical sections on biomedical information; neural data analysis; neural network models; recommender systems; time series analysis.
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| 505 |
0 |
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|a Intro -- Preface -- Organization -- Contents -- Part III -- Biomedical Information -- Classification of Neuroblastoma Histopathological Images Using Machine Learning -- 1 Introduction -- 2 Methodology -- 2.1 Dataset -- 2.2 Experimental Setup -- 3 Results -- 4 Discussion -- 5 Conclusion -- References -- Data Mining ENCODE Data Predicts a Significant Role of SINA3 in Human Liver Cancer -- 1 Introduction -- 2 Methods -- 3 Results -- 3.1 Co-location of TFBS Analysis -- 3.2 HBV-transfection Effect on Histone Modification -- 4 Discussion -- References
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| 505 |
8 |
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|a Diabetic Retinopathy Detection Using Multi-layer Neural Networks and Split Attention with Focal Loss -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Proposed Approach -- 3.2 Dataset -- 3.3 Data Pre-processing -- 3.4 Metrics for Performance Evaluation -- 4 Experimental Results and Discussion -- 5 Analysis -- 6 Conclusion -- References -- Enhancer-DSNet: A Supervisedly Prepared Enriched Sequence Representation for the Identification of Enhancers and Their Strength -- 1 Introduction -- 2 Materials and Methods -- 3 Proposed Enhancer-DSNet Methodology -- 4 Benchmark Dataset
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| 505 |
8 |
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|a 5 Evaluation Metrics -- 6 Experimental Setup and Results -- 6.1 Results -- 7 Conclusion -- References -- Machine Learned Pulse Transit Time (MLPTT) Measurements from Photoplethysmography -- 1 Introduction -- 2 Design -- 2.1 Machine Learned Pulse Transit Time -- 2.2 HeartPy Pulse Transit Time -- 3 Analysis -- 3.1 Methods -- 4 Results -- 4.1 BIDMC Patient 6 Drilldown -- 5 Discussion -- 5.1 Limitations -- 6 Conclusion -- References -- Weight Aware Feature Enriched Biomedical Lexical Answer Type Prediction -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Pre-processing
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| 505 |
8 |
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|a 3.2 Feature Selection -- 3.3 LAT Prediction -- 4 Experimental Study -- 4.1 Dataset and Experiment Configuration -- 4.2 Evaluation Metrics and Baseline -- 4.3 Results and Discussion -- 5 Conclusion and Future Work -- References -- Neural Data Analysis -- Decoding Olfactory Cognition: EEG Functional Modularity Analysis Reveals Differences in Perception of Positively-Valenced Stimuli -- 1 Introduction -- 2 Methodology -- 2.1 Recruitment of Participants -- 2.2 Experimental Protocol -- 2.3 EEG Data Acquisition and Preprocessing -- 2.4 EEG Data Analysis -- Community Detection -- 3 Results
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| 505 |
8 |
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|a 3.1 Partitioning the Functional Connectivity Networks -- 3.2 Inter-module Metrics -- 3.3 Intra-module Metrics -- 4 Discussion -- 4.1 Alterations in the Inter-module Metrics in the Community Functional Connectivity Organisation -- 4.2 Variations in the Intra-module Metrics in the Community Functional Connectivity Organisation -- 5 Conclusions -- A Appendix: Anatomical Segregation of ROIs in Communities -- References -- Identifying Motor Imagery-Related Electroencephalogram Features During Motor Execution -- 1 Introduction -- 2 Method -- 2.1 Experiment and Preprocessing Procedure
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|a Includes author index.
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| 588 |
0 |
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|a Online resource; title from PDF title page (SpringerLink, viewed February 3, 2021).
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| 650 |
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|a Neural networks (Computer science)
|v Congresses.
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| 650 |
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0 |
|a Pattern perception.
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| 650 |
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|a Machine learning.
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| 650 |
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|a Database management.
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| 650 |
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|a Application software.
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|a Neural networks (Computer science)
|2 fast
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|a Application software
|2 fast
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|a Database management
|2 fast
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|a Machine learning
|2 fast
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|a Pattern perception
|2 fast
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| 655 |
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|a proceedings (reports)
|2 aat
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|a Conference papers and proceedings
|2 fast
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|a Conference papers and proceedings.
|2 lcgft
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| 655 |
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|a Actes de congrès.
|2 rvmgf
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| 700 |
1 |
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|a Yang, Haiqin.
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| 700 |
1 |
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|a Pasupa, Kitsuchart.
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| 700 |
1 |
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|a Leung, Chi Sing.
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| 700 |
1 |
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|a Kwok, James
|c (Professor of Computer Science and Engineering)
|1 https://id.oclc.org/worldcat/entity/E39PCjtTFmKxpH87XhJVRYpMKb
|
| 700 |
1 |
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|a Chan, Jonathan H.
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| 700 |
1 |
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|a King, Irwin,
|d 1961-
|1 https://id.oclc.org/worldcat/entity/E39PCjFkGyQMYRYbGC9y4JJgPP
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| 758 |
|
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|i has work:
|a Neural information processing (Text)
|1 https://id.oclc.org/worldcat/entity/E39PCGYM6rx99wVHV4KfgtvVwd
|4 https://id.oclc.org/worldcat/ontology/hasWork
|
| 776 |
0 |
8 |
|i Print version:
|a Yang, Haiqin.
|t Neural Information Processing : 27th International Conference, ICONIP 2020, Bangkok, Thailand, November 23-27, 2020, Proceedings, Part III.
|d Cham : Springer International Publishing AG, ©2020
|z 9783030638351
|
| 830 |
|
0 |
|a Lecture notes in computer science ;
|v 12534.
|
| 830 |
|
0 |
|a LNCS sublibrary.
|n SL 1,
|p Theoretical computer science and general issues.
|
| 856 |
4 |
0 |
|u https://holycross.idm.oclc.org/login?auth=cas&url=https://link.springer.com/10.1007/978-3-030-63836-8
|y Click for online access
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| 903 |
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|a SPRING-COMP2020
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| 994 |
|
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|a 92
|b HCD
|