Computational Intelligence in Communications and Business Analytics : 6th International Conference, CICBA 2024, Patna, India, January 23–25, 2024, Revised Selected Papers, Part II / / edited by Jyoti Prakash Singh, Maheshwari Prasad Singh, Amit Kumar Singh, Somnath Mukhopadhyay, Jyotsna K. Mandal, Paramartha Dutta

• Autore: Singh Jyoti Prakash
• Pubblicazione: Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025
• Edizione: 1st ed. 2025.
• Descrizione fisica: 1 online resource (453 pages)
• Disciplina: 005.73; 003.54
• Soggetto topico: Data structures (Computer science); Information theory; Computer engineering; Computer networks; Artificial intelligence; Application software; Data Structures and Information Theory; Computer Engineering and Networks; Computer Communication Networks; Artificial Intelligence; Computer and Information Systems Applications
• Altri autori: SinghMaheshwari Prasad SinghAmit Kumar MukhopadhyaySomnath MandalJyotsna K DuttaParamartha
• Nota di contenuto: 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.
• Sommario/riassunto: 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.
• Titolo autorizzato: Computational Intelligence in Communications and Business Analytics
• ISBN: 9783031813399; 3031813391
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910983481703321
• Lo trovi qui: Univ. Federico II
• Serie: Communications in Computer and Information Science, . 1865-0937 ; ; 2367