Produktbild: Soft Computing and Its Engineering Applications
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Soft Computing and Its Engineering Applications 6th International Conference, icSoftComp 2024, Bangkok, Thailand, December 10–12, 2024, Revised Selected Papers, Part I

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

16.05.2025

Abbildungen

XX, 190 illus., 135 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen

Herausgeber

Kanubhai K. Patel + weitere

Verlag

Springer

Seitenzahl

419

Maße (L/B/H)

23,5/15,5/2,4 cm

Gewicht

663 g

Sprache

Englisch

ISBN

978-3-031-88038-4

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

16.05.2025

Abbildungen

XX, 190 illus., 135 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen

Herausgeber

Verlag

Springer

Seitenzahl

419

Maße (L/B/H)

23,5/15,5/2,4 cm

Gewicht

663 g

Sprache

Englisch

ISBN

978-3-031-88038-4

Herstelleradresse

Springer-Verlag GmbH
Tiergartenstr. 17
69121 Heidelberg
DE

Email: GPSR Kontakt

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  • Produktbild: Soft Computing and Its Engineering Applications
  • .- Theory and Methods.

    .- A Prediction-Enabled Scheduling Framework for Cloud Manufacturing Applications.

    .- Evaluating the need of Reinforcement Learning by implementing Heuristic Algorithms with its Load Balancing and Performance Testing in Cloud.

    .- Optimizing XGBoost for Blockchain Malicious Node Detection by Metaheuristics.

    .- A Correct-by-Construction Model for Request-Based Access Control.

    .- Lattice-based Post Quantum Cryptography using Variations of Learning with Error (LWE).

    .- A Spatio-Temporal Explainable Deep Learning Approach for Frame Classification from Book Flipping Videos.

    .- Adapting a Modern Siamese Framework for 360° Video Object Tracking.

    .- Detecting Deepfake Images with Enhanced Generative Adversarial Networks.

    .- CRITIC and TOPSIS-Enhanced Fuzzy Clustering (CTEFC) Protocol for IoT-Based WSNs.

    .- Ambiguous sets and various distance measurements.

    .- The Study on Face recognition using Between Convolutional Neural Network (CNN) and Local Binary Histogram (LBPH) with Censored Facial Images.

    .- An Air-written Real-time English Isolated Numeral Recognition.

    .- The PV-ALE Dataset: Enhancing Apple Leaf Detection and Classification Through Transfer Learning with Convolutional Neural Networks.

    .- Impact of SMOGN on Regression Models for Crop Yield Prediction in Mizoram Agriculture.

    .- Deep Learning for Sustainable Apple Farming: Disease Detection in Leaves.

    .- Forecasting Coffee Prices with Facebook Prophet: A Machine Learning

    Approach.

    .- Enhancing Hindi Named Entity Recognition using XLM-RoBERTa.

    .- Neural Network Architectures for Machine Translation: Enhancing Quality Education through Improved Access to Multilingual Resources.

    .- Optimizing Error Detection in Generated Code Using Metaheuristic Optimized Natural Language Processing.

    .- Enhancing Graph Based Models For Automatic Program Repair.

    .- Enhancing Grapheme-to-Phoneme Conversion for Bengali Speech Recognition: Leveraging Dialectical Variations and Morphophonemic Rules.

    .- Determinants of Generative AI-based Chatbot Adoption in Customer Support.

    .- ToxNet: A Multi-layer Network Approach to Toxicity Analysis using

    Graph Neural Networks.

    .- Multiphase Sentiment Analysis Model for Automatic Movie Reviews.

    .- An Interpretable Deep Learning Framework For Brain Tumor Diagnosis using UNET and CAM Techniques.

    .- Connecting the Dots: Understanding the Influence of Online Social Networks on Mental Wellness via Social Network Analysis.

    .- Drug target identification using integrative multi-omics data analysis and deep learning - a breast cancer case study.

    .- A Stack Ensemble Model for Paralysis Prediction from Lower Limb EMG Signals using Machine Learning Approaches.

    .- Lung Cancer Detection using Deep-Learning models.

    .- Inclusive Innovation: Early Detection Strategy for Lung Cancer Using Ensembles.

    .- Psychological State Analysis for Technostress Detection: A Hierarchical Clustering Approach.