Machine Learning, Image Processing, Network Security and Data Sciences

7th International Conference, MIND 2025, Jaipur, India, December 12–14, 2025, Proceedings, Part I
Erscheinungsjahr 2026
ISBN: 978-3-032-31232-7
Verlag: Springer

Buch, Englisch, 570 Seiten, Format (B × H): 155 mm x 235 mm

Reihe: Communications in Computer and Information Science

This two-volume set CCIS 2980-2981 constitutes the revised selected papers of the 7th International Conference on Machine Learning, Image Processing, Network Security and Data Sciences, MIND 2025, held in Jaipur, India, during December 12–14, 2025.

The 84 full papers included in these volumes were carefully reviewed and selected from 406 submissions. They are organized in topical sections as follows: Artificial Intelligence and Intelligent Systems; and Networks and Communication Systems.

Zielgruppe

Research

Autoren/Hrsg.

Verma, Gyanendra Kumar

Doriya, Rajesh

Buckchash, Himanshu

Fachgebiete

• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Algorithmen & Datenstrukturen
• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Informationstheorie, Kodierungstheorie
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Mathematik | Informatik EDV | Informatik Informatik Bildsignalverarbeitung
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Mathematik | Informatik EDV | Informatik Technische Informatik

Inhaltsverzeichnis

.- Artificial Intelligence and Intelligent Systems.

.- Visual and Local Explanations for Trustworthy AI for Autism Detection for Asian Data.

.- Hybrid Graph–Language Embedding Framework for Citation-Aware Sentiment 
Analysis.

.- AI-driven Anomaly Detection in Avionics Systems using Isolation Forest.

.-  Integrating Postmortem Reports and Embedding Techniques for Fault Prediction.

.- Coverage  Precision  and Fairness in Association-Rule Mining: Evidence from 
Treadmill.

.-  Demonstrating Quantum Advantage in GANs: A Comparative Study on Diabetes 
Healthcare Data.

.-  A Hybrid Deep Learning Approach for Automated Plant Disease Diagnosis in Indian 
Ridge Gourd: Dataset Creation and Real-World Application.

.- Experimental Study on Tea Plant Disease Classification.

.- Multiscale Recursive Attention Guided Deep Feature Fusion Network for Haze 
Removal.

.- Deepfake Video Detection using CNN Deep Learning Architectures.

.- Crop-Specific Hyperparameter Optimization for Machine Learning-Based Yield 
Prediction of Kharif Crops: Rice  Wheat  and Maize.

.- Enhancing Real-Time Through-Wall Imaging with a Hybrid Signal Processing and 
Convolutional Neural Network Approach.

.- Advanced Kalman Filtering for Video-Based Tremor Assessment in Parkinson’s 
Chapter 1. Disease: Comparative Analysis with Deep Learning Classification.

.- LightGraph: Efficient Multi-modal Sparse Graph Attention Network for Crisis 
Tweet Classification.

.-  TTMFN: A Time-aware Transformer-based Multimodal Fusion Network for 
Depression Detection from Social Media.

.- Synthetic Images Generation for Skin Cancer Using Conditional Generative 
Adversarial Network with Explanation.

.- Evaluating Privacy Risks in Machine Unlearning: A Comprehensive Audit of 
Unlearned and Retained Samples.

.- Adaptive Edge-Cloud Orchestration: A Serverless Paper on Intelligent ML 
Application Placement with Hybrid Resource Feedback.

.-  Explainable Mortality Outcome Prediction Using Neuro-Symbolic Causal 
Reasoning.

.-  Enhanced Class Imbalance-Aware Skin Cancer Classification.

.- Glaucoma detection using deep learning.

.- Temporal Stability in Semi-Supervised Label Propagation: A Lightweight 
Regularization Framework.

.- Enhancing Cardiovascular Care Using IoT Data and CatBoost Machine Learning 
Model.

.-  Image-Based Multi-Class Classification of Diabetic Retinopathy Using Deep 
Learning.

.-  MoTANet: A Hybrid MobileNetV2–Transformer Attention Network for Multi-Crop 
Disease Classification.

.- Ano-HQNN: Hybrid Quantum Neural Network for Enhanced Anomaly Detection in 
Surveillance Videos.

.-  Efficient Handwriting Recognition for Person  Identification Using Lightweight 
and Deep CNN  Model.

.- Choosing the Right Optimizer and Loss Function: A Deep Learning Perspective on 
Hyperspectral Image Classification.

.- A Lightweight LiDAR-Only Path Planning Framework for Formula Student 
Driverless Racecar.

.-  Bridging the Communication Divide: Sign  Language in Online Meetings  Kulkarni.

.- Transformer-Enhanced Residual U-Net for Automated Dental Plaque 
Segmentation in Clinical Intraoral Imagery.

.- DEV3NET: A Two-Stage Deep Learning Approach for Automated Occlusion Mask 
Generation and Facial Segmentation.

.- Deepfake Face Detection using an Ensemble of Multiple Deep Learning Models  
Kavad  Meet.

.-  Knowledge-Grounded Canonical SMILES Generation via RAG-enhanced Large 
Language Models.

.- A Mastery-Guided Retrieval-Augmented Generation for Grounded Tutoring.

.-  Data-Driven Rockfall Assessment using Synthetic Training and CNN–XGBoost 
Integration.

.- SpeechComp-FSQ: A Transformer-Based Model for Efficient Speech Compression.

.- Ensemble Deep Learning with a Trainable Meta-Learner for Enhanced Semantic 
Segmentation of Informal Settlements.

.- Linguistic Network Analysis of Psychopathology Dimensions in Adolescence: A 
Cognitive Neuropsychological Approach.

.-  Cross Attentive Multimodal Fusion Network Using Deep Learning Models and 
Transformers for Driver Drowsiness Detection.

.- Human Pose Estimation for Cricket Shot Classification: Machine Learning and 
Deep Learning Perspectives.

.-  Automated Seizure Classification from Raw Intracranial EEG Using a Transformer 
Encoder.

.-  A Multi-Metric Decomposed Mode Selection for Phase-Based EEG Recurrence 
Analysis in Major Depressive Disorder (INVITED).