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Sharma / Bansal / Saraswat

Intelligent Learning for Computer Vision

Proceedings of Congress on Intelligent Systems 2020

Medium: Buch
ISBN: 978-981-334-584-3
Verlag: Springer Nature Singapore
Erscheinungstermin: 21.05.2022
Lieferfrist: bis zu 10 Tage

This book is a collection of selected papers presented at the First Congress on Intelligent Systems (CIS 2020), held in New Delhi, India, during September 5–6, 2020. It includes novel and innovative work from experts, practitioners, scientists, and decision-makers from academia and industry. It covers selected papers in the area of computer vision. This book covers new tools and technologies in some of the important areas of medical science like histopathological image analysis, cancer taxonomy, use of deep learning architecture in dental care, and many more. Furthermore, this book reviews and discusses the use of intelligent learning-based algorithms for increasing the productivity in agricultural domain.


Produkteigenschaften


  • Artikelnummer: 9789813345843
  • Medium: Buch
  • ISBN: 978-981-334-584-3
  • Verlag: Springer Nature Singapore
  • Erscheinungstermin: 21.05.2022
  • Sprache(n): Englisch
  • Auflage: 1. Auflage 2021
  • Serie: Lecture Notes on Data Engineering and Communications Technologies
  • Produktform: Kartoniert
  • Gewicht: 908 g
  • Seiten: 591
  • Format (B x H x T): 155 x 235 x 33 mm
  • Ausgabetyp: Kein, Unbekannt
Autoren/Hrsg.

Herausgeber

Development of Inter-Ethnic Harmony Search Algorithm based on Inter-Ethnic Reconciliation.- A Low-Cost Embedded Computer Vision System for the Classification of Recyclable Objects.- An Optimal Feature Selection Approach based on IBBO for Histopathological Image Classification.- Accuracy Evaluation of Plant Leaf Disease Detection and Classification using GLCM and Multiclass SVM Classifier.- A Deep Learning Technique for Automatic Teeth Recognition in Dental Panoramic X-Ray Images  Using Modified Palmer Notation System.- Detection of Parkinson’s disease from hand-drawn images using Deep Transfer Learning.- An Empirical Analysis of Hierarchical and Partition Based Clustering Techniques in Optic Disc Segmentation.- Multi Class Support Vector Machine Based Household Object Recognition System Using Features Supported by Point Cloud Library.- Initialization of MLP Parameters using Deep Belief Networks for Cancer Classification.- An Improved Inception Layer Based Convolutional Neural Network For Identifying Rice Leaf Diseases.- Design & Implementation of Traffic Sign Classifier Using Machine Learning Model.- Designing controller parameter of wind turbine emulator using artificial bee colony algorithm.- Text-Document Orientation Detection Using Convolutional Neural Networks.- A Deep Learning based Segregation of Housing Image data for Real Estate application.