Data Science, AI and Applications

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.