UID:
almahu_9949387855702882
Umfang:
XXIV, 385 p. 141 illus., 118 illus. in color.
,
online resource.
Ausgabe:
1st ed. 2022.
ISBN:
9783031194962
Serie:
Lecture Notes in Artificial Intelligence, 13613
Inhalt:
The two-volume set LNAI 13612 and 13613 constitutes the proceedings of the 21st Mexican International Conference on Artificial Intelligence, MICAI 2022, held in Monterrey, Mexico, in October 2022. The total of 63 papers presented in these two volumes was carefully reviewed and selected from 137 submissions. The first volume, Advances in Computational Intelligence, contains 34 papers structured into three sections: Machine and Deep Learning Image Processing and Pattern Recognition Evolutionary and Metaheuristic Algorithms The second volume contains 29 papers structured into two sections: Natural Language Processing Intelligent Applications and Robotics.
Anmerkung:
Machine and Deep Learning -- Skipped Nonsynaptic Backpropagation for Interval-valued Long-term Cognitive Networks -- Cross-target Stance Classification as Domain Adaptation -- Impact of loss function in Deep Learning methods for accurate retinal vessel segmentation -- Embedded Implementation of the Hypersphere Neural Network for Energy Consumption Monitoring -- MACFE: A Meta-learning and Causality Based Feature Engineering Framework -- Time Series Forecasting with Quantum Machine Learning Architectures -- Explainable Model of Credit Risk Assessment Based on Convolutional Neural Networks -- Reinforcement Learning with Success Induced Task Prioritization -- Cooperative Chaotic Exploration with UAVs Combining Pheromone Dispersion and Hopfield Chaotic Neural Network -- Machine Learning-based Decision Making in Evolutionary Multiobjective Clustering -- RBF Neural Network Based on FT-Windows for Auto-Tunning PID Controller -- Pursuing the Deep-Learning-based Classification of Exposed and Imagined Colors from EEG -- Data Stream Mining for Dynamic Student Modeling -- CESAMMO: Categorical Encoding by Statistical Applied Multivariable Modeling -- Heart Failure Disease Prediction Using Machine Learning Models -- Classification of flood warnings applying a convolutional neural network -- Machine Learning Techniques in Credit Default Prediction -- Convolutional and dense ANN for cloud kinetics fore-casting using satellite images -- The role of the number of examples in Convolutional Neural Networks with Hebbian Learning -- Image Processing and Pattern Recognition -- Vision-based Gesture Recognition for Smart Light Switching -- On the generalization capabilities of FSL methods through domain adaptation: a case study in endoscopic kidney stone image classification -- A Novel Hybrid Endoscopic Dataset for Evaluating Machine Learning-based Photometric Image Enhancement Models -- Comparison of automatic prostate zones segmentation models in MRI images using U-net-like architectures -- Towards an interpretable model for automatic classification of endoscopy images -- Reversible image authentication scheme with tampering reconstruction based on very deep super resolution network -- Improving artefact detection in endoscopic video using a real-time ensemble method -- White Blood Cell Detection and Classification in Blood Smear Images Using a One-Stage Object Detector and Similarity Learning -- Evolutionary and Metaheuristic Algorithms -- Towards A Complete Multi-Agent Pathfinding Algorithm For Large Agents -- Analysis Of The Anytime MAPF Solvers Based On The Combination Of Conflict-Based Search (CBS) and Focal Search (FS) -- Studying Special Operators for the Application of Evolutionary Algorithms in the Search of Optimal Boolean Functions for Cryptography -- Unification of Source-Code Re-use Similarity Measures -- Considerations in the Incremental Hypervolume Algorithm of the WFG -- A Hybrid Hyperheuristic Approach for the Containership Stowage Problem Considering the Ship Stability -- Mathematical optimization model for raw sugar unloading delay from harbor to storage silos.
In:
Springer Nature eBook
Weitere Ausg.:
Printed edition: ISBN 9783031194955
Weitere Ausg.:
Printed edition: ISBN 9783031194979
Sprache:
Englisch
DOI:
10.1007/978-3-031-19496-2
URL:
https://doi.org/10.1007/978-3-031-19496-2
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