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|n (1st :
|d 2019 :
|c Sibpur, India)
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1 |
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|a Computational intelligence in pattern recognition :
|b proceedings of CIPR 2019 /
|c Asit Kumar Das, Janmenjoy Nayak, Bighnaraj Naik, Soumen Kumar Pati, Danilo Pelusi, editors.
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3 |
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|a CIPR 2019
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1 |
|a Singapore :
|b Springer,
|c [2020]
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4 |
|c ©2020
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| 300 |
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|a 1 online resource (1023 pages)
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|a text
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|a text file
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|a Advances in Intelligent Systems and Computing Ser. ;
|v v. 999
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| 588 |
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|a Print version record.
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0 |
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|a Intro; Organizing Committee; Chief Patron; Patrons; Honorary Advisory Chair; Honorary General Chair; General Chair; Program Chair; Organizing Chair; International Advisory Committee; National Advisory Committee; Technical Committee; Publicity Chair; Logistic Chair; Convenors; Publication Chair; Finance Chair; CIPR Reviewers; Preface; Acknowledgements; About the Conference; Contents; About the Editors; On the Synthesis of Unate Symmetric Function Using Memristor-Based Nano-Crossbar Circuit; 1 Introduction; 2 Proposed Method; 3 Experimental Result and Analysis; 4 Conclusion; References
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| 505 |
8 |
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|a A Novel Enhancement and Segmentation of Color Retinal Image Based on Fuzzy Measure and Fuzzy Integral1 Introduction; 2 Methodology; 2.1 Fuzzy Image Enhancement; 2.2 Fuzzy Image Segmentation; 3 Result and Analysis; 4 Conclusion; References; On the Cryptanalysis of S-DES Using Binary Cuckoo Search Algorithm; 1 Introduction; 2 Preliminaries; 2.1 The S-DES Algorithm Description; 2.2 The Cuckoo Search Algorithm; 2.3 Binary Cuckoo Search Algorithm; 2.4 Cost Function; 3 Proposed Method; 4 Experiments and Results; 5 Conclusion and Future Works; References
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| 505 |
8 |
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|a Feature Selection Using NSGA-II for Event Extraction on Genetic and Molecular Mechanisms Involved in Plant Seed Development1 Introduction; 2 Motivation; 3 Proposed Approach; 4 Major Steps for Event Extraction; 4.1 Segmentation and Tokenization; 4.2 Feature Extraction; 4.3 Feature Selection Using NSGA-II; 4.4 Generate Classifiers for Each Event Type; 4.5 Merge the Classifiers for Each Event Type; 4.6 Selection of Event Type from the Result of Classifiers; 5 Features; 6 Experimental Results and Analysis; 6.1 Dataset; 6.2 Result; 6.3 Error Analysis; 6.4 Comparison with Existing Systems
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|a 7 ConclusionReferences; Detection and Identification of Parasite Eggs from Microscopic Images of Fecal Samples; 1 Introduction; 2 Literature Survey; 3 Proposed System; 3.1 Preprocessing; 3.2 Object Segmentation; 3.3 Feature Extraction; 3.4 Classification; 4 Result and Discussion; 5 Conclusion and Future Work; References; Identification of Some Transposable Elements of DNA Using "BP Suche" Algorithm; 1 Introduction; 1.1 Coding Region of DNA; 1.2 Open Reading Frame (ORF); 1.3 Noncoding DNA; 2 Brief Background of Transposon; 3 Methodology; 4 Result and Discussion; 5 Conclusion; References
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| 505 |
8 |
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|a An Approach for Sentiment Analysis of GST Tweets Using Words Popularity Versus Polarity Generation1 Introduction; 2 Preparing GST Tweets Corpus; 2.1 Feature I: Tweet Model; 3 Data Preprocessing; 3.1 Coverage with State-of-the-Art Lexicons; 4 Popularity Versus Polarity; 4.1 Feature II: Popularity-Polarity Modeling; 4.2 Visualization; 5 Observations; 6 Conclusion and Future Work; References; Smart Health Monitoring System for Temperature, Blood Oxygen Saturation, and Heart Rate Sensing with Embedded Processing and Transmission Using IoT Platform; 1 Introduction; 2 System Architecture
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|a 2.1 Input Unit
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| 520 |
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|a This book presents practical development experiences in different areas of data analysis and pattern recognition, focusing on soft computing technologies, clustering and classification algorithms, rough set and fuzzy set theory, evolutionary computations, neural science and neural network systems, image processing, combinatorial pattern matching, social network analysis, audio and video data analysis, data mining in dynamic environments, bioinformatics, hybrid computing, big data analytics and deep learning. It also provides innovative solutions to the challenges in these areas and discusses recent developments.
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| 650 |
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|a Pattern recognition systems
|v Congresses.
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| 650 |
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|a Computational intelligence
|v Congresses.
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| 650 |
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7 |
|a Computational intelligence
|2 fast
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| 650 |
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|a Pattern recognition systems
|2 fast
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| 655 |
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|a proceedings (reports)
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|a Conference papers and proceedings
|2 fast
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| 655 |
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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 Das, Asit Kumar
|c (Computer scientist)
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| 700 |
1 |
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|a Nayak, Janmenjoy.
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| 700 |
1 |
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|a Naik, Bighnaraj.
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| 700 |
1 |
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|a Pati, Soumen Kumar.
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| 700 |
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|a Pelusi, Danilo.
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| 758 |
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|i has work:
|a Computational Intelligence in Pattern Recognition (Text)
|1 https://id.oclc.org/worldcat/entity/E39PCXXpvphb9G8PmmfwHB7xH3
|4 https://id.oclc.org/worldcat/ontology/hasWork
|
| 776 |
0 |
8 |
|i Print version:
|a Das, Asit Kumar.
|t Computational Intelligence in Pattern Recognition : Proceedings of CIPR 2019.
|d Singapore : Springer, ©2019
|z 9789811390418
|
| 830 |
|
0 |
|a Advances in intelligent systems and computing ;
|v 999.
|
| 856 |
4 |
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|u https://holycross.idm.oclc.org/login?auth=cas&url=https://link.springer.com/10.1007/978-981-13-9042-5
|y Click for online access
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|a SPRING-ROBOTICS2020
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| 994 |
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