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Author:   Shivakumara Palaiahnakote ,  Rajesh Palit ,  Mo Saraee ,  Pradeep K. Atrey
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
ISBN:  

9783032113344

ISBN 10:   3032113342
Pages:   500
Publication Date:   03 January 2026
Audience:   College/higher education ,  Professional and scholarly ,  Postgraduate, Research & Scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Not yet available  
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Table of Contents

Part-vol-I. .- Deep Learning-Based Potato Leaf Disease Classification Using a Custom CNN. .- Enhanced Rice Leaf Diseases Classification Using ResNet50 on a Bangladeshi Dataset. .- AI-Driven Multilayered Cybersecurity Intelligence Framework for Critical Infrastructure Protection. .- Enhancing Candidate Selection with NLP-Driven Resume Analysis for Industry 4.0 Recruitment Systems. .- Clothes-Changing Person Re-identification with Unique Identity-Specific Attribute Details. .- MAST-GCN: Multi-Part Attention-Guided Spatial-Temporal GCN Approach for Gait-Based Person Recognition. .- Evaluation of CNNs for Flower Classification: A Study on Computational Efficiency and Model Performance. .- A Transformer based approach for Real-Time Sentiment Analysis of Transliterated Bengali Text. .- Automated Classification of Husk Species Using DenseNet121 and Vision Transformer. .- Attention-Driven Ensemble Learning: Enhancing Diabetes Prediction in Data-Scarce Environments. .- Interpretable IoT-Enabled Machine Learning Framework on Optimized Climate Information for Crop Yield and Resource Usage. .- Comprehensive Predictive Insights: Leveraging Clinical Data for Hepatitis C Prediction with Machine Learning and Deep Learning. .- A Systematic Taxonomy of Neural Network  Architectures:  Principles, Trade-offs, and Future Directions. .- Predicting and Explaining Fatal Road Casualty Types in Great Britain: A Comparative Analysis of Machine Learning, Deep Learning, and Transformers. .- Obstructive Sleep Apnea Detection using 1D CNN-LSTM approach. .- Fusing ResNet50 and VGG16 for Enhanced Diagnosis of Acute Lymphoblastic Leukemia: A MultiNet Ensemble Approach. .- Deriving Biologically Relevant Rules in Breast Cancer Subtypes using FP-Growth Algorithm. .- EEG-Based Depression Detection Using CNNs and Heatmaps. .- Deep Learning-Enhanced OCT Image Analysis Pipeline: Integrating Denoising, Super-Resolution, and Fuzzy Logic for Improved Clinical Diagnostics. .- Understanding Public Perceptions and Behaviours Towards COVID-19 Vaccination: A Multifaceted Analysis. .- Early Thyroid Disease Diagnosis Using a Hybrid Ensemble Learning Approach with Feature Selection, SMOTE, and Model Explainability. .- Preprocessed Lung Data Evaluation Using SVM for Superior Cancer Diagnosis. .- A Deep Learning Approach for Detecting Pests and Diseases in Maize Crops. .- Privacy-Preserving Prediction of Chronic Kidney Disease Using Ensemble Machine Learning with Laplacian Differential Privacy and Explainable AI. .- Channel Attention Mechanism in Hybrid Deep Learning Model for Accurate Brain Tumor Classification. .- Hybrid Artificial Intelligence for Forecasting Renewable Energy Consumption with Ensemble Machine Learning and Time Series Models. .- Optimizing American Sign Language Recognition with Binarized Neural Networks: A Comparative Study with Traditional Models. .- An Explainable and Ensemble Approach for Skin Lesion Classification Using Attention-Based Lightweight CNNs. .- Handling Imbalanced Datasets with Real-World Positive Samples in Dengue Prediction Using Machine and Deep Learning Models. .- FAKD-XAI: Feature-Aligned Knowledge Distillation with Explainable AI for Efficient Brain Tumor Classification. .- Advancing Web-based Bilingual Spam Detection System  with XLM-RoBERTa: Dataset Creation and Model Fine-Tuning. .- An Interpretable Hybrid Framework for Brain Tumor Classification: Fusion of EfficientNetV2L, ViTs, and Attention Mechanisms. .- Moment Detection at Scale: Dataset-Driven Techniques for Temporal Localization. Part-vol-II. Part-vol-III.

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