Applications of Computational Intelligence 6th IEEE Colombian Conference, ColCACI 2023, Bogota, Colombia, July 26-28, 2023, Revised Selected Papers /

This book constitutes the refereed proceedings of the 6th IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2023, held in Bogota, Colombia during July 2023. A total of 11 full papers were carefully reviewed and selected from 42 submissions. They were organized in topic...

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Соавтор: SpringerLink (Online service)
Другие авторы: Orjuela-Cañón, Alvaro David (Редактор), Lopez, Jesus A. (Редактор), Arias-Londoño, Julián David (Редактор)
Формат: Электронный ресурс eКнига
Язык:английский
Опубликовано: Cham : Springer Nature Switzerland : Imprint: Springer, 2024.
Редактирование:1st ed. 2024.
Серии:Communications in Computer and Information Science, 1865
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Online-ссылка:https://doi.org/10.1007/978-3-031-48415-5
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505 0 |a Biomedical Applications -- A Transfer Learning Scheme for COVID-19 Diagnosis from Chest X-Ray Images using Gradient-weighted Class Activation Mapping -- On the Comparison of Multilayer Perceptron and Extreme Learning Machine for Pedaling Recognition using EEG -- Self-supervised deep-learning segmentation of corneal endothelium specular microscopy images -- Tuberculosis Drug Discovery Estimation Process by Using Machine and Deep Learning Models -- Biological Applications -- A Robust Hybrid Control Approach tuned by PSO for Long-Time Delay Nonlinear Chemical Processes -- Feature selection of the spectral signature of cocoa bean based on visible and near-infrared spectroscopy for cadmium estimation -- On the use of Deep Learning Models for Automatic Animal Classification of Native Species in the Amazon -- Engineering Applications -- Intra-day Electricity Price Forecasting Based on a Time2Vec-LSTM Model -- Radio Frequency Pattern Matching – Subscriber Location in 5G Networks -- Robotic Arm based on Artificial Intelligence for Learning Braille as an Inclusive Tool in Educational Environments -- Spatial shrinkage prior: A probabilistic approach to model for categorical variables with many levels. . 
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