Computational Intelligence in Communications and Business Analytics : 7th International Conference, CICBA 2025, Kolkata, India, July 4-6, 2025, Revised Selected Papers, Part I (Communications in Computer and Information Science 2861) (2026. Approx. 1050 p. 235 mm)

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Computational Intelligence in Communications and Business Analytics : 7th International Conference, CICBA 2025, Kolkata, India, July 4-6, 2025, Revised Selected Papers, Part I (Communications in Computer and Information Science 2861) (2026. Approx. 1050 p. 235 mm)

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Full Description

This three-volume set CCIS 2861-2863 constitutes the refereed proceedings of the 7th International Conference on Computational Intelligence in Communications and Business Analytics, CICBA 2025, held in Kolkata, India, during July 4-6, 2025.

The 100 full papers presented in these volumes were carefully reviewed and selected from 311 submissions. The papers are organized into thematic tracks as follows:Computational Intelligence; Data Communication; and Analytics and Application.

Contents

.- Computational Intelligence Track

.- Multi-Scale Attention Transformer Efficient Network (MATE-Net) for Polyp Segmentation.
.- Enhancing Disease Prediction using Advanced Machine Learning Algorithms.
.- An Efficient Approach for Determining Optimal Number of Clusters using Binary Search and Cluster Validity Indices.
.- Using Features of Differential Dermal Potentials to Distinguish Sport Performers from Non-performers.
.- DLR-CovNet: Dual-Scale Lightweight Residual Network for Efficient COVID-19 Classification.
.- An Automated Approach for Temporal Attack Graph Dataset Generation.
.- Comparative Analysis of Abstractive Summarization Models for Clinical Radiology Reports.
.- A Correlation Guided Deep Feature Selection from Chest X-Ray Images: A Case Study on Automatic Detection of Pneumonia and COVID-19.
.- Harnessing the True Potential of LLMs: Iterative Self-Improvement for Competitive Performance.
.- Multimodal Retrieval of Scientific Articles by Integrating Textual and Visual Embeddings.
.- Enhanced Skin Cancer Detection Using a Hybrid CNN-Transformer Model with Attention Mechanism.
.- Harris Hawk Optimization for Rumor Detection on Social Media Using Machine Learning and Explainable AI Techniques.
.- Closing the Lexical-Semantic Divide: A Unified Approach for Retrieval-Augmented Generation.
.- Sensor-Based Activity Classification for Health Monitoring of Elderly People using a Deep Convolutional Neural Network.
.- Advancement of Supervised Machine Learning Algorithms for Risk Assessment in the Insurance Industry.
.- An Approach to Named Entity Recognition for Aviation Text.
.- Adaptive Multimodal Threat Detection Using Hybrid Graph Convolutional Transformers and Dynamic Harris Hawks Optimization.
.- A Hybrid Soft Computing Framework for Emotion-Driven Crime Prediction Using Multi-Modal Intelligence.
.- Comparative Analysis of Machine Learning Techniques for Classification of Millet Seeds.
.- Structural Integrity: A Smart Model for Construction Health Monitoring Based on Event-B.
.- Enhanced AI Framework for Precise Crater Detection and Planetary Surface Analysis.
.- Blockchain Node Intelligence based on Decentralized Framework.
.- BioFusionNet: A Practical Approach for Deepfake Detection.
.- Leveraging Custom Scalable CNN Framework for Efficient Plant Disease Classification.
.- AVENT: A Virtual Reality-Based Teleconferencing Application.
.- Real-Time Driver Drowsiness Detection Using CNN-Based Eye Blink Analysis for Accident Prevention.
.- Vision-Based Augmentative and Alternative Communication (AAC) System for Eye-Blink-Based Communication in Individuals with Paralysis.
.- Transfer Learning-based Deep Feature Resampling for Imbalanced Leaf Disease Classification.
.- A Comparative Analysis of Transformer-Based Rainfall-Runoff Modeling with Adam and RAdam Optimization Techniques.
.- Identify Researchers' Credibility on Citation using Self-Citation Detection by Author Name Disambiguation.
.- Meta-Analysis in Agricultural Research: Unveiling Climate Change Impacts on the Yields Gap Studies.
.- Brain tumor segmentation using enhanced and improved ResUNet++.

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