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Peer Review Policy

All submissions undergo rigorous peer review.

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Hybrid CNN-Transformer; Image classification; Vision Transformers; Multi-head self-attention; Local feature extraction Explainable Reinforcement Learning; Deep Q-Network; SHAP Explanations; Autonomous Decision-Making; Policy Interpretability Federated Learning; Differential Privacy; Secure Aggregation; Healthcare Data Analytics; Privacy-Preserving Machine Learning Generative Adversarial Networks; Medical Image Synthesis; Data Augmentation; Chest X-ray Imaging; Image Quality Evaluation Low-Resource Languages; Zero-Shot Learning; Few-Shot Learning; Prompt Engineering; Large Language Models. Graph Neural Networks; Social Network Analysis; Knowledge Graph Completion; Graph Convolutional Networks; Graph Attention Networks; Link Prediction; Node Classifcation TinyML; Edge Object Detection; Model Optimization; Microcontroller Deployment; Quantization and Pruning Multimodal Emotion Recognition; Feature Fusion; Convolutional Neural Networks; Long Short-Term Memory; Human–Computer Interaction Smart Agriculture; Predictive Analytics; Crop Yield Prediction; Pest Detection; Machine Learning and Deep Learning Models Transformer-Based Code Generation; Software Optimization; Code Intelligence; Automated Programming; Structure-Aware Encoder Adversarial Robustness; Defense Mechanisms; Adversarial Attacks; Certified Robustness; Deep Neural Networks Precision Medicine; Genomic–Clinical Data Fusion; Deep Learning; Multi Modal Fusion Network (MMFN); Patient Outcome Prediction Industrial Internet of Things; Unsupervised Representation Learning; Variational Autoencoder; Anomaly Detection; Predictive Maintenance Trustworthy AI; Causal Inference; Interpretability; Machine Learning; Explainable AI Ethical AI; Fairness; Explainable AI; Sustainable AI; Bias Mitigation

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