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Intelligent Computing Systems: Third International Symposium, ISICS 2020, Sharjah, United Arab Emirates, March 18–19, 2020, Proceedings: Communications in Computer and Information Science, cartea 1187

Editat de Carlos Brito-Loeza, Arturo Espinosa-Romero, Anabel Martin-Gonzalez, Asad Safi
en Limba Engleză Paperback – 11 mar 2020
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.
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Specificații

ISBN-13: 9783030433635
ISBN-10: 3030433633
Pagini: 151
Ilustrații: X, 151 p. 83 illus., 64 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.24 kg
Ediția:1st ed. 2020
Editura: Springer International Publishing
Colecția Springer
Seria Communications in Computer and Information Science

Locul publicării:Cham, Switzerland

Cuprins

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.