Third International Symposium, ISICS 2020, Sharjah, United Arab Emirates, March 18-19, 2020, Proceedings Redaktion: Brito-Loeza, Carlos; Safi, Asad; Martin-Gonzalez, Anabel; Espinosa-Romero, Arturo
Third International Symposium, ISICS 2020, Sharjah, United Arab Emirates, March 18-19, 2020, Proceedings Redaktion: Brito-Loeza, Carlos; Safi, Asad; Martin-Gonzalez, Anabel; Espinosa-Romero, Arturo
Sie sind bereits eingeloggt. Klicken Sie auf 2. tolino select Abo, um fortzufahren.
Bitte loggen Sie sich zunächst in Ihr Kundenkonto ein oder registrieren Sie sich bei bücher.de, um das eBook-Abo tolino select nutzen zu können.
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.
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.
Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.
Die Herstellerinformationen sind derzeit nicht verfügbar.
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.
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.
Es gelten unsere Allgemeinen Geschäftsbedingungen: www.buecher.de/agb
Impressum
www.buecher.de ist ein Internetauftritt der buecher.de internetstores GmbH
Geschäftsführung: Monica Sawhney | Roland Kölbl | Günter Hilger
Sitz der Gesellschaft: Batheyer Straße 115 - 117, 58099 Hagen
Postanschrift: Bürgermeister-Wegele-Str. 12, 86167 Augsburg
Amtsgericht Hagen HRB 13257
Steuernummer: 321/5800/1497
USt-IdNr: DE450055826