Overview

This volume CCIS 2189 constitutes the refereed proceedings of the 12th Conference, JCC-BD&ET 2024, held  in La Plata, Argentina during June 25–27, 2024.   The 12 full papers presented were carefully reviewed and selected from 37 submissions. They were categorized under the topical sections as follows:  Parallel and Distributed Computing, Machine and Deep Learning, Smart Cities and E-Government, Visualization, Emerging Topics, Innovation in Computer Science Education, Computer Security.

Full Product Details

Author:   Marcelo Naiouf ,  Laura De Giusti ,  Franco Chichizola ,  Leandro Libutti
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   2024 ed.
Volume:   2189
ISBN:  

9783031708060

ISBN 10:   3031708067
Pages:   176
Publication Date:   11 October 2024
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Not yet available  
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Table of Contents

Parallel and Distributed Computing.- Fast genomic data compression on multicore machines.- Machine and Deep Learning.- Deep Learning based instance segmentation of Neural Progenitor Cell nuclei in fluorescence microscopy images.- Deep Learning based instance segmentation of Neural Progenitor Cell nuclei in fluorescence microscopy images.- CB-RISE Improving the RISE interpretability method through Convergence Detection and Blurred Perturbations.- Wavelength Calibration of Historical Spectrographic Plates With Dynamic Time Warping.- An Empirical Method for Processing IO Traces to Analyze the Performance of DL Application.- Smart Cities and E-Government.- Industry 5.0. Digital Twins in the process industry A bibliometric análisis.- Visualization.- An ABMS COVID19 Propagation Model for Hospital Emergency Departments.- Emerging Topics.- QuantumUnit A proposal for classic multi qubit assertion development.- Tool for quantum classical software lifecycle.- Innovation in Computer Science Education.- Strategies to predict students exam attendance.- Computer Security.- Prediction of TCP Firewall Action Using Different Machine Learning Models.

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