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|a Mexican International Conference on Artificial Intelligence
|n (20th :
|d 2021 :
|c Mexico City, Mexico)
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| 245 |
1 |
0 |
|a Advances in computational intelligence :
|b 20th Mexican International Conference on Artificial Intelligence, MICAI 2021, Mexico City, Mexico, October 25-30, 2021, Proceedings.
|n Part I /
|c Ildar Batyrshin, Alexander Gelbukh, Grigori Sidorov (eds.).
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| 246 |
3 |
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|a MICAI 2021
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| 260 |
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|a Cham :
|b Springer,
|c 2021.
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| 300 |
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|a 1 online resource (433 pages)
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| 336 |
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|a text
|b txt
|2 rdacontent
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| 337 |
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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| 347 |
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|a text file
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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 artificial intelligence
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| 490 |
1 |
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|a Lecture notes in computer science ;
|v 13067
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| 490 |
1 |
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|a LNCS sublibrary: SL 7, Artificial intelligence
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| 505 |
0 |
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|a Intro -- Preface -- Conference Organization -- Contents -- Part I -- Contents -- Part II -- Machine and Deep Learning -- Identifying Optimal Clusters in Purchase Transaction Data -- 1 Introduction -- 2 Clustering Taxonomies -- 3 Cluster Validity Indices -- 4 Data Complexity Measures -- 5 Data Sets and Experimental Methodology -- 6 Results and Discussions -- 7 Conclusions -- A Appendix -- References -- Artificial Organic Networks Approach Applied to the Index Tracking Problem -- 1 Introduction -- 1.1 Objectives and Limitations -- 2 The Proposed Approach -- 2.1 AON Properties
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| 505 |
8 |
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|a 2.2 Artificial Hydrocarbon Networks Algorithm -- 3 Implementation Considerations -- 3.1 System Identification -- 3.2 Target Function Mathematical Formulation -- 3.3 Financial Analysis and Strategy -- 4 Preliminary Results -- 4.1 Experiment 1: Establishing a Regression -- 4.2 Experiment 2: Comparing MNLR Performance Vs. Other ML Techniques. -- 4.3 Experiment Three: Buy-and-Hold Strategy -- 4.4 Experiment 4: A Hybrid K-Means with AHN Algorithm -- 5 Conclusions and Future Work -- References -- Supervised Learning Approach for Section Title Detection in PDF Scientific Articles -- 1 Introduction
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| 505 |
8 |
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|a 2 Related Works -- 3 Methodology -- 3.1 Dataset Creation -- 3.2 Classifiers Training and Testing -- 4 Results -- 5 Conclusion -- References -- Real-Time Mexican Sign Language Interpretation Using CNN and HMM -- 1 Introduction -- 2 Related Work -- 2.1 Methods -- 2.2 Techniques -- 2.3 Works About MSL in Mexico -- 3 Proposal -- 4 Dataset -- 4.1 Description -- 4.2 Participants -- 4.3 Data Acquisition -- 4.4 Dataset Standardization -- 5 Experiments and Results -- 5.1 Training -- 5.2 Results Experiment 1: Focus on Isolated Words -- 5.3 Results Experiment 2: Focus on Sentences -- 6 Conclusions
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| 504 |
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|a References-RiskIPN: Pavement Risk Database for Segmentation with Deep Learning-1 Introduction-2 Databases-2.1 Previous Datasets-2.2 RisksIPN-3 Segmentation Deep Model-4 Experiments and Results-4.1 Preprocessing-4.2 Training-5 Conclusion-References-A Comparative Study on Approaches to Acoustic Scene Classification Using CNNs-1 Introduction-2 Related Work-3 Methodology-3.1 Data Organization and Collection-3.2 Data Augmentation-3.3 Feature Representations-3.4 Development of CNNs-4 Results and Evaluation-5 Conclusion-References.
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| 505 |
8 |
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|a Measuring the Effect of Categorical Encoders in Machine Learning Tasks Using Synthetic Data -- 1 Introduction -- 2 General Methodology -- 2.1 Real-World Datasets -- 2.2 Synthetic Datasets -- 3 Experimental Results -- 3.1 Real-World Dataset -- 3.2 Synthetic-Datasets -- 4 Conclusions -- Appendix -- References -- Long-Term Exploration in Persistent MDPs -- 1 Introduction -- 2 Related Work -- 3 Background -- 3.1 Markov Decision Processes -- 3.2 Persistent MDPs -- 4 Exploration via State Space Clustering -- 4.1 Similarity Model -- 4.2 Graph of Clusters -- 5 The Prince of Persia Domain -- 6 Experiments
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|a 6.1 Experimental Setup.
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|a Includes author index.
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|a The two-volume set LNAI 13067 and 13068 constitutes the proceedings of the 20th Mexican International Conference on Artificial Intelligence, MICAI 2021, held in Mexico City, Mexico, in October 2021. The total of 58 papers presented in these two volumes was carefully reviewed and selected from 129 submissions. The first volume, Advances in Computational Intelligence, contains 30 papers structured into three sections: Machine and Deep Learning Image Processing and Pattern Recognition Evolutionary and Metaheuristic Algorithms The second volume, Advances in Soft Computing, contains 28 papers structured into two sections: Natural Language Processing Intelligent Applications and Robotics.
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| 588 |
0 |
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|a Online resource; title from PDF title page (SpringerLink, viewed November 3, 2021).
|
| 650 |
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0 |
|a Artificial intelligence
|v Congresses.
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| 650 |
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7 |
|a Artificial intelligence
|2 fast
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| 655 |
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|a Electronic books.
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| 655 |
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7 |
|a proceedings (reports)
|2 aat
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| 655 |
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|a Conference papers and proceedings
|2 fast
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| 655 |
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7 |
|a Conference papers and proceedings.
|2 lcgft
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| 655 |
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7 |
|a Actes de congrès.
|2 rvmgf
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| 700 |
1 |
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|a Batyrshin, Ildar.
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| 700 |
1 |
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|a Gelbukh, Alexander,
|d 1962-
|1 https://id.oclc.org/worldcat/entity/E39PBJtGWRDXgQKMd7tYHv6BT3
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| 700 |
1 |
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|a Sidorov, Grigori.
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| 758 |
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|i has work:
|a Advances in computational intelligence Part I (Text)
|1 https://id.oclc.org/worldcat/entity/E39PCFRtjKrqFftgvvpDq6Wftq
|4 https://id.oclc.org/worldcat/ontology/hasWork
|
| 776 |
0 |
8 |
|i Print version:
|a Batyrshin, Ildar.
|t Advances in Computational Intelligence.
|d Cham : Springer International Publishing AG, ©2021
|z 9783030898168
|
| 830 |
|
0 |
|a Lecture notes in computer science.
|p Lecture notes in artificial intelligence.
|
| 830 |
|
0 |
|a Lecture notes in computer science ;
|v 13067.
|
| 830 |
|
0 |
|a LNCS sublibrary.
|n SL 7,
|p Artificial intelligence.
|
| 856 |
4 |
0 |
|u https://holycross.idm.oclc.org/login?auth=cas&url=https://link.springer.com/10.1007/978-3-030-89817-5
|y Click for online access
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| 903 |
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|a SPRING-COMP2021
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| 994 |
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|a 92
|b HCD
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