Computational Intelligence in Communications and Business Analytics
Springer International Publishing (Verlag)
978-3-031-81338-2 (ISBN)
- Noch nicht erschienen - erscheint am 28.01.2025
- Versandkostenfrei
- Auch auf Rechnung
- Artikel merken
This three-volume set CCIS 2366-2368 constitutes the refereed proceedings of the 6th International Conference on Computational Intelligence in Communications and Business Analytics, CICBA 2024, held in Patna, India, during January 23-25, 2024.
The 82 full papers presented in this volume were carefully reviewed and selected from 249 submissions. Together, these papers showcase cutting-edge research in the fields of computational intelligence and business analytics, covering a broad range of topics.
Computational Intelligence II.- Multimodal Skin Cancer Classification Optimized Convolutional Network with Customized Loss and RNN Based FCNN Fusion.- Deep Learning Based MLP Model in Detection of Cotton Plant Leaf Disease.- Enhancing Drug Candidate Generation Comparing Genetic Algorithm And WGAN GP Approaches.- Predicting Employee Job Satisfaction by Using Vector Space Model.- Simplernn Based Human Emotion Recognition Using EEFG Signals.- Improving Melanoma Classification Using Transfer Learning Based Wavelet Features.- Research Challenges and Future Perspective in Semantic Segmentation of Brain Stroke Lesions in Magnetic Resonance Imaging.- Revolutionizing Suicide Ideation Detection in Social Media An Ensemble Optimized Bi GRU With Attention Approach.- A Computer Vision Model Utilizing Autoencoders for Surface Defect Recognition.- A Study on the Impact of Partitioning on Community Detection in Graph Networks.- Load Combination Optimization for Trailer Design using Genetic Algorithm.- Features Extraction from Android Apps Using Reverse Engineering.- Efficient Near Infrared Spectroscopy Based Feature Selection of Tannic Acid for Black Tea Evaluation.- Taming the Monkeypox Outbreak with Deep Learning for Skin Lesion Detection.- A Comprehensive Review of AI based Low Back Pain Assessment and Rehabilitation.- Analysis of Multidomain Abstractive Summarization Using Salience Allocation.- Detection and Localization of Malignant Cells from Surgical Images for Robot Assisted Invasive Surgery using Deep Learning.- An Intelligent Integrated Prediction Based Approach for Heart Disease Detection A Comprehensive Study.- Multi Modal Approach for Ethereum Smart Contract Vulnerability Detection.- Kcst Net Deep Learning Based Classification of Kidney Diseases Using CT Images.- High Yield Model Compression Paradigms for Low Footprint Signal Classification Supplementing Resource Constrained Embedded Environments.- Regularizing CNNs using Confusion Penalty Based Label Smoothing for Histopathology Images.- Leveraging Generative Pre Trained Models and Discriminative Pre Trained Language Models for Sentiment Analysis.- Advancing Lung Cancer Diagnosis and Prognosis through Machine Learning Algorithm.- Influent sewage water classification using machine learning.- Fine grained Image Classification on Skin Cancer Dataset.- Learning based soiling loss estimation in solar panels and solar panel soiling database generation.- CNN ML Framework Based Predominant Musical Instrument Recognition Using Mel Spectrogram.
Erscheint lt. Verlag | 28.1.2025 |
---|---|
Reihe/Serie | Communications in Computer and Information Science |
Zusatzinfo | XII, 266 p. |
Verlagsort | Cham |
Sprache | englisch |
Maße | 155 x 235 mm |
Themenwelt | Informatik ► Theorie / Studium ► Algorithmen |
Schlagworte | Agriculture technology • Artificial Intelligence • cryptography • cybersecurity • Data Augmentation • Deep learning • disease detection • energy efficiency • generative models • Healthcare Prediction • Human Activity Recognition • image classification • IoT (Internet of Things) • machine learning • Medical Imaging • Natural Language Processing (NLP) • sentiment analysis • Smart Systems • Speech Recognition • stock price prediction |
ISBN-10 | 3-031-81338-3 / 3031813383 |
ISBN-13 | 978-3-031-81338-2 / 9783031813382 |
Zustand | Neuware |
Haben Sie eine Frage zum Produkt? |
aus dem Bereich