Intelligent Computing Systems

Third International Symposium, ISICS 2020, Sharjah, United Arab Emirates, March 18¿19, 2020, Proceedings
Herausgegeben:Brito-Loeza, Carlos; Espinosa-Romero, Arturo; Martin-Gonzalez, Anabel; Safi, Asad

• Broschiertes Buch

Produktbeschreibung

This book constitutes the proceedings of the Third International Symposium on Intelligent Computing Systems, ISICS 2020, held in Sharjah, United Arab Emirates, in March 2020.
The 13 full papers presented in this volume were carefully reviewed and selected from 46 submissions. They deal with the field of intelligent computing systems focusing on artificial intelligence, computer vision and image processing.

Produktdetails

• Communications in Computer and Information Science 1187
• Verlag: Springer / Springer International Publishing / Springer, Berlin
• Artikelnr. des Verlages: 978-3-030-43363-5
• 1st ed. 2020
• Seitenzahl: 164
• Erscheinungstermin: 11. März 2020
• Englisch
• Abmessung: 235mm x 155mm x 10mm
• Gewicht: 260g
• ISBN-13: 9783030433635
• ISBN-10: 3030433633
• Artikelnr.: 58789801

Inhaltsangabe

An Investigation on Performance of Attention Deep Neural Networks in Rapid Object Recognition.- Breast Cancer Detection and Localization using MobileNet based Transfer Learning for Mammograms.- U-Net based Glioblastoma Segmentation with Patient's Overall Survival Prediction.- MicroPython or Arduino C for ESP32 - Efficiency for Neural Network Edge Devices.- Analysis of Frameworks for Traffic Agent Simulations.- Blockchain-based Authentication Approach for Securing Transportation System.- A classification model for modeling online articles.- A Novel Feature Extraction Model to Enhance Underwater Image Classification.- A Comprehensive Analysis of MRI Based Brain Tumor Segmentation using Conventional and Deep Learning Methods.- Sentiment Analysis on Predicting Presidential Election: Twitter Used Case.- Convolutional Neural Network U-Net for Trypanosoma cruzi Segmentation.- Segmentation of Echocardiographic Images in Murine Model of Chagas Disease.- Lung Cancer patient's survival Prediction Using GRNN-CP.