Advanced Network Technologies and Intelligent Computing: 5th International Conference, ANTIC 2025, Gwalior, India, December 21–23, 2025, Proceedings, Part II(2921 Communications in Computer and Information Science)

This book constitutes the refereed proceedings of the 5th International Conference on Advanced Network Technologies and Intelligent Computing, ANTIC 2025, held in Gwalior, India, during December 21–23, 2025.

The 97 full papers and 7 short papers included in these volumes were carefully reviewed and selected from 585 submissions. They were organized in topical sections as follows: Advance Network Technologies; and Intelligent Computing.

.- Deep Learning based Leaf Disease Detection, Prevention, and Treatment Prediction Application for Smart Agriculture.
.- An Attention based CNN for Plant Leaf Disease Detection.
.- Improvising the performance of Transcutaneous Electroacupuncture Stimulation (TEAS) Induced EEG Classification using Optimal Band selection and Sequential Ridge Regression.
.- Reinforcement Learning based on TD-3 for the Nonlinear Model of CSTR: Temperature Tracking.
.- Advanced Short-Term Load Forecasting for the Indian Grid: A Hybrid Convolutional and Recurrent Neural Network Approach.
.- To Be, Not to Be, or Both: A Quantum Leap for Sentiment Analysis.
.- Deep Learning-based Defect Detection in Agricultural Crops: A Comprehensive Approach.
.- Multi-Class Classification of Chronic Renal Disease (CRD)  using Deep Convolutional Neural Network (CNN) Model.
.- HeLa CELL DETECTION AND SEGMENTATION USING DIGITAL IMAGE PROCESSING METHODS.
.- An Efficient CNN-Based Method for Detecting Driver Drowsiness from Facial Images.
.- Explainable AI-driven Transcriptome Analysis of Drug Responses for Therapeutic Discovery and Safety Evaluation in Cardiovascular Diseases.
.- Hybrid Fractal-Deep Learning Model for Time Series Prediction: A Comparative Study.
.- Finding the Signal: A Deep Dive into Data Augmentation  and Transformer Performance for Hope Speech Detection.
.- An intelligent approach to artificial speech detection and identification based on KNN.
.- ROI-RONI-Based Reversible Data Hiding Algorithm for Medical Images  Using Huffman Compression and DWT-LSB Embedding.
.- Modeling Recurrent Neural Networks in Serial Recall Paradigm With Dynamic Self-Excitation.
.- SegVCR-LISA: Commonsense Reasoning in VLMs through Segment-Specific Instruction Tuning.
.- A Domain-Aware Grievance Redressal System Leveraging RAG and Open-Source LLMs.
.- Brain Tumour Segmentation using Multi-Orientation Two-Pathway CNN with Attention-Based Fusion in MRI Images.
.- Adaptive MOHAN Activation for Enhanced Brain Tumor Segmentation Using TransUNet and Grad-CAM++.
.- MULTI-STRATEGY FEATURE FUSION FRAMEWORK FOR PLANT DISEASE DIAGNOSIS.
.- LeafGuard: A Deep Learning Framework for Disease Detection in Apple Orchards.
.- An Effective AI-Driven Prompting Approach for Video Summarization System using Flan-T5 Model.
.- A comparative analysis of CNN, BiLSTM and Hybrid CNN-BiLSTM for Air Quality Index.
.- Interpretable Feature Selection for Breast Cancer Diagnosis: A Comparative Study of ElasticNet and SHAP.
.- Assessment of Brassica Napus L. Yield Attributes under Varied Concentrations of Untreated Distillery Effluent through Fuzzy Rule Based Modelling.
.- OtoscopeNet: An Efficient and Attention-Driven Deep Learning Framework for Robust Diagnosis of Ear Diseases.
.- Hybrid Mask Fusion and Transformer-Driven Deep Feature Analysis for Multi-Class Chest X-Ray Diagnosis.
.- TinyEyeNet: An Efficient CNN for Classifying Anterior Segment Eye Conditions.
.- A Comparative Analysis of Deep Learning Models for Early Prediction of Alzheimer’s Disease using structural MRI.
.- Attention-ResUNet for Automated Fetal Head Segmentation.
.- Advancing Vision-based Human Action Recognition: Exploring Vision-Language CLIP Model for Generalisation in Domain-Independent Tasks.
.- Explainable Hybrid Deep Learning for Medicinal Leaf Disease Classification: R50-MViT with LIME and Grad-CAM Interpretability.
.- Green Channel Enhanced Self Attention U-Net++ for Multi-Lesion Retinal Segmentation with Uncertainty-Guided Explainability in Diabetic Retinopathy.