Smart Technologies and Intelligent Computing

Optimizing text classification: Particle swarm approach to random forests

Deep learning approaches for reliable object detection under adverse weather

IoT-based water pipeline leakage detection system

Handwritten examination evaluation using LLMs and GenAI

Deep retinex-inspired enhancement of low-light lunar images using dark-bright image pairs

Solar irradiation component forecasting using ANN framework with diverse configuration of meteorological parameters

Quantum-enhanced machine learning for predictive catalysis: A unified framework for transition metal complex activity forecasting

Voice-based Parkinson’s disease prediction using machine learning

Artificial Intelligence for hand gesture to speech conversion

Predictive modeling for cervical cancer detection using machine learning

A hybrid CNN-transformer model for multi-marker detection in cerebrovascular disease using multimodal imaging

Advancing lung cancer prediction: A comparative study of ML, DL and hybrid models

Enhancement in HTM-CLA for credit card fraud detection using H-DS and H-MSC classifier

Multi-model learning system using EfficientNet classifier for malnutrition management

AI-driven healthcare management system

Handwritten digit recognition using deep learning

Real time trespassing detection using YOLOv5 and ONXX deployed through a streamlit web application

AWS-enabled centralized bus booking system: A scalable and efficient cloud-based solution

Common salts classification using Raman spectroscopy and deep learning

Well mind: AI-powered mental health monitoring and prediction

DeepFrontal: Deep learning-based 3D face reconstruction from 2D views

YOLOv11-based emergency vehicle detection

Deep learning-based facial emotion recognition system

Hybrid-DS-SCNet: Lightweight module for facial emotion detection

Fine-tuned transformer models with explainability for Android malware detection

Evaluating feature importance in AI-driven crop water stress models

Screening of pulmonary embolism using large language model

Enhanced cloud service ranking using a hybrid RoBERTa-based deep learning framework with multi-criteria decision support

Deep ensemble framework for robust classification of pulmonary diseases from radiographs

Optimized serverless cloud-based real-time processing architecture for sensor data analytics in healthcare

Crop yield stack: A multi-model ensemble approach for enhanced agriculture forecasting

Investigating long-term impact through AI insights and 5g innovation integration

GenAI for automated medical reports: A retrieval-augmented framework

GRFAT-MH: A privacy-preserving AI Tutor for mental health support in rural classrooms

Machine learning-based land-use and land-cover classification using Google Earth Engine over a part of Haryana, India

Comparative analysis for calorie burn prediction using machine learning techniques

Deep learning for brain tumor segmentation-comparison of architectures and activation functions

Hardware-software co-design for energy efficient machine learning on FPGA

Real-time plant disease identification via CNN-based leaf image classification and mobile deployment

Hybrid deep learning approach for brain tumor detection using ResNet and EfficientNet

FoodScanAI: A dual-modal deep learning system for food spoilage detection using synthetic sensor data and image classification

Y-PN-MSSD-based yogic meditation for psycho-oncology subject with kyphosis

Hybrid deep-cuckoo framework for robust brain tumor detection and segmentation in MRI scans

A real-time forest fire detection and alert system using deep learning and satellite imagery

Optimized hybrid machine learning techniques for predictive analysis of lung cancer

Machine learning-based prediction and recommendation system for anxiety and depression

Early identification of Alzheimer’s disease: Leveraging support vector machines for predictive insights

Privacy-preserving techniques in data anonymization and masking: Trends and challenges

An efficient edge-based segmentation model with correlation weighted linked feature vector for melanoma detection using VGG16

Detection of epileptic seizures in EEG signals: Analysis of linear time-domain features using classical machine learning techniques

Early diagnosis and detection of Parkinson’s disease using AI

IoT-enhanced vehicle monitoring solution with intuitive mobile application for AI-based Android and iOS devices

A novel framework for improving cloud IoT efficiency with virtualized networks

Transformer-based deep learning approach for channel estimation in MIMO wireless systems

Leveraging VGG19 for accurate detection of apple plant diseases

Energy efficient data aggregation and adaptive compression model with reduced loss levels in wireless sensor networks

Low-cost wireless EMG-controlled prosthetic arm using 3D printing

Comparative analysis of legal text summarization using transformer-based models

Blockchain for ethical AI model Validation

Lw-CovidNet: Lightweight deep-learning module for disease prediction in CT scan images

Intelligent mental health monitoring in the workplace: A deep learning perspective

Novel seismic neural network approach for robust intrusion detection using texture-based features

AI-driven big data analytics: Unveiling insights for next-gen intelligent systems

A hybrid neuro-fusion model for network intrusion detection using non-symmetric deep autoencoders and transformer-augmented gradient boosting

Zero- and few-shot Arabic text summarization using retrieval-augmented generation

Smart beekeeping monitoring system using IoT and machine learning

SoilSense: Soil quality prediction using real-time LSTM-GNN

Silent video to text: CNN-based deep learning model for lip movement recognition and transcription

Explainable deep learning models for ECG classification using CNN, LSTM, and BiLSTM architectures

Early breast cancer detection using integrated feature selection and quad-learner ensemble based hunting–tracking optimization

Deep learning CNN model-based stock price prediction by candle stick images 520

Class imbalance handling and metaheuristic optimization of XGBoost for breast cancer detection

Quantum-secure authentication and robust retrieval for remote sensing

A reduced analytical review of intelligent IoT security: Trends, gaps, and future challenges

Deep learning-based road damage detection and severity assessment using explainable AI

Neural architecture search for real-time object detection in drone navigation

Advancing patient outcomes in Indian healthcare through AI-enabled diagnostic and communication systems

Artificial Intelligence and Blockchain-enabled privacy in assistive technologies for disability empowerment

Deep neural networks for the diagnosis of Parkinson’s disease through visual feature learning

Hybrid attention network with TabNet benchmarking for breast cancer and heart disease classification

Log Gabor and wavelet-based transform for enhanced CT MRI image fusion

Assessing risks to children’s privacy in smart toys within intelligent communication systems

Smart technologies and intelligent computing for AI-driven gesture recognition in rehabilitation, yoga, and learning

Bias detection and mitigation in large language models: A fairness-driven approach

Context-aware local querying model using Llama 3 and DeepSeek R1

Meta-modeling for cardiovascular risk prediction

AI-driven models for accountability and transparency in public sector administration

Evaluating the effectiveness of advanced LSTM variants in weather forecasting prediction models

Leveraging AI for intelligent decision-making in space mission planning

A hybrid CNN–transformer framework with self-supervised and federated learning for privacy-preserving cardiovascular disease diagnosis

A unified ontology-based and semantic interoperability framework for smart agriculture systems

Human-in-the-loop: A hybrid orchestration model for intelligent automation

Multiclass brain tumor classification using vision transformer

AI-powered customer support chatbot leveraging feedforward neural network architecture

Quantum-inspired federated learning framework for real time IoT cybersecurity

Cyberbullying detection through image classification: D-Net architecture

Optimized YOLO model to control traffic flow dynamically by analysing traffic density and conditions

Sentiment analysis on social networking data using NLP and deep learning

AI-Driven IoT framework for smart health monitoring using embedded sensors and edge analytics

Tomato leaf disease detection and classification using CNN with Grad-CAM

Deep feature fusion and hybrid CNN-SVM architecture for reliable and explainable drug toxicity prediction

Biography

Jaskaran Singh, Dean Research and Head of the School of Forensic Science at Geeta University, Panipat, is an accomplished academic and researcher. An INSPIRE Fellow (DST, India) and Gold Medalist in Forensic Science, he has guided multiple Ph.D. and master’s scholars. Dr. Singh has published over 35 research papers in reputed Scopus and ABDC-indexed journals, authored five books, and holds 25 patents, including three granted. A motivational speaker and international trainer, he has delivered over 100 workshops, conferences, and expert sessions across India and abroad, contributing significantly to research, training, and knowledge dissemination.

Meenu Gupta (Stanford’s Top 2% Scientists, 2025) is a Professor and Head of Conferences & Research Outreach (Engineering Cluster) in the UIE-CSE Department at Chandigarh University, India. She is currently pursuing her Postdoctoral Fellowship at the MIR Lab, USA, and holds a Ph.D. in Computer Science and Engineering from Ansal University, Gurgaon (2020). With over 17 years of teaching and research experience, her expertise spans Machine Learning, Intelligent Systems, Data Mining, Artificial Intelligence, Image Processing, Smart Cities, Data Analysis, and Brain–Machine Interaction (BMI). Dr. Gupta has edited 22+ books and authored four engineering books. She has published over 250 research papers in reputed international journals and conferences, along with 45+ book chapters. She actively serves as a reviewer for several high-impact journals, including Big Data, Artificial Intelligence Review, Scientific Reports, CMC, and Digital Health. She is a Senior Member of IEEE, Life Member of ISTE and IAENG, and currently an Executive Committee Member of IEEE Delhi Section as well as Advisor of the IEEE RAS Chapter. She has also organized numerous conferences technically sponsored by IEEE Delhi Section, IEEE CIS, AIP, and others, contributing significantly to advancing research outreach and collaborations.

Rakesh Kumar is an Associate Director at the UIE-CSE Department, Chandigarh University, Punjab, India. He is pursuing his Post Doc Fellowship from MIR lab, USA. He has completed his Ph.D. in Computer Science and Engineering from Punjab Technical University, Jalandhar, 2017. He has more than 22 years of teaching experience. His research interests are IoT, Machine Learning, and Natural Language Processing. He has edited over 12 books with reputed publishers and has authored five books. He works as a reviewer for several journals, including Big Data, CMC, Scientific Reports, TSP, Multimedia Tools and Applications, IEEE Access, etc. He is a Senior Member of IEEE. He has authored or co-authored more than 200 publications in various national/ international conferences and journals. He is also an organiser and editor of many international conferences under the aegis of IEEE and AIP.