Proceedings of International Conference on Innovations in Software Architecture and Computational Systems [E-Book] : ISACS 2021 /

Proceedings of International Conference on Innovations in Software Architecture and Computational Systems [E-Book] : ISACS 2021 / edited by Jyotsna Kumar Mandal, Somnath Mukhopadhyay, Aynur Unal, Santanu Kumar Sen.

This book gathers a collection of high-quality peer-reviewed research papers presented at First International Conference on Innovations in Software Architecture and Computational Systems (ISACS 2021), held at Guru Nanak Institute of Technology, Kolkata, India, during 2 - 3 April 2021. The book prima...

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Mandal, Jyotsna Kumar, editor
Mukhopadhyay, Somnath, editor / Sen, Santanu Kumar, editor / Unal, Aynur, editor
1st edition 2021.
Singapore : Springer, 2021
XI, 244 pages 91 illustrations, 59 illustrations in color (online resource)
englisch
9789811643019
10.1007/978-981-16-4301-9
Studies in Autonomic, Data-driven and Industrial Computing
Artificial intelligence.
Computational intelligence.
Computer engineering.
Computer software.
Embedded computer systems.
Internet of things.
Microprocessors.



  • Text to Image Classification using Attn: Gan With Dense Net Architecture
  • Cyclone Detection and Forecasting Using Deep Neural Networks through Satellite Data
  • An Improved Differential Evolution Scheme for Multilevel Image Thresholding Aided with Fuzzy Entropy
  • Clustered Fault Repairing Architecture for 3D ICs using Redundant TSV
  • The Implementation of Similarity Measures in Group Decision-Making Problems by Signless Laplacian Energy of an Intuitionistic Fuzzy Graph
  • Uniform Grid Formation by Asynchronous Fat Robots
  • A LSB Substitution based Steganography Technique using DNA Computing for Color Images
  • An Approach of Safe Stock Prediction using Genetic Algorithm
  • Suicide Ideation Detection in Online Social Networks: A Comparative Review
  • An Improved K-Means Algorithm for Effective Medical Image Segmentation
  • Breast Cancer Histopathological Image Classification using Convolutional Neural Networks
  • A Framework for Predicting Placement of a Graduate using Machine Learning Techniques.