Del i serien Communications in Computer and Information Science

Applications of Computational Intelligence

6th IEEE Colombian Conference, ColCACI 2023, Bogota, Colombia, July 26-28, 2023, Revised Selected Papers

Häftad, Engelska, 2023

AvAlvaro David Orjuela-Cañón,Jesus A Lopez,Julián David Arias-Londoño

939 kr

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?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.

Produktinformation

Utgivningsdatum2023-11-18
Mått155 x 235 x 11 mm
Vikt289 g
FormatHäftad
SpråkEngelska
SerieCommunications in Computer and Information Science
Antal sidor174
FörlagSpringer International Publishing AG
ISBN9783031484148

Tillhör följande kategorier

Systemvetenskap och AI inom Data och IT
Artificiell intelligens inom Data och IT

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.