MITIGATING MODE COLLAPSE TO IMPROVE DIVERSITY IN TEXT-TO-IMAGE GAN OUTPUTS: STRATEGIES IN ARCHITECTURAL DESIGN, TRAINING METHODOLOGIES, AND EVALUATION TECHNIQUES SUBUHI KASHIF ANSARI, MANAL AL KHAMMASH, ANJALI APPUKUTTAN, ANNE ANOOP, SANDEEP KUMAR MATHARIYA, SHEELA D V, MOHAMMED SALEH AL ANSARI Journal of Theoretical and Applied Information Technology, 2026 Text-to-image generation using Generative Adversarial Networks (GANs) has advanced significantly in recent years. This enables image synthesis from textual descriptions. However, mode collapse remains a critical challenge that limits output diversity. This systematic review analyzes strategies to mitigate mode collapse in text-to-image GANs. It examins architectural designs, training methodologies, latent-space techniques, and evaluation metrics. The review covers 45 studies published between 2015 and 2025, categorized into: architectural innovations (18 papers), training-based strategies (12 papers), latent-space and loss function methods (10 papers), and evaluation-centric approaches (5 papers). Findings show that attention-based models, multi-scale architectures, and semantic-spatial models enhance semantic alignment and diversity, with specific limitations. Training-based approaches, including curriculum learning, adaptive training, gradient penalties, and progressive growing of GANs, help stabilize training and mitigate collapse. Latent-space techniques, such as mode-seeking losses, contrastive losses, and noise manipulation, promote output diversity. However, evaluation metrics like Fréchet Inception Distance (FID), Inception Score (IS), Learned Perceptual Image Patch Similarity (LPIPS), and Multi-Scale Structural Similarity Index (MS-SSIM) show limitations in capturing semantic diversity. Progress in mitigating mode collapse depends on combined architectural design, training stability, and loss-function engineering. Future priorities include developing unified benchmarks for evaluating semantic diversity, exploring hybrid architectures, and designing adaptive training protocols to enable more robust text-to-image models generating diverse, semantically coherent outputs.
Meta Learning Enhanced Graph Transformer for Robust Smart Grid Anomaly Detection Layth Almahadeen, Aseel Smerat, Sandeep Kumar Mathariya, G. Indra Navaroj, Vuda Sreenivasa Rao, Kamila Ibragimova, Osama R.Shahin International Journal of Advanced Computer Science and Applications, 2025 The increasing complexity of modern smart grids and the heterogeneity of multi-sensor data make anomaly detection extremely challenging, as existing techniques struggle to capture long-range spatial dependencies, cross-sensor interactions, and unseen anomaly patterns. Conventional models such as Isolation Forest, Random Forest, GCAD, AT-GTL, CVTGAD, and hybrid CNN-Transformer approaches often suffer from limited generalization, weak multimodal fusion, and strong dependence on labeled anomalies. To address these limitations, this study introduces a novel Multimodal Graph Transformer with Contrastive Self-Supervised Learning and Model-Agnostic Meta-Learning (MGT-CGSSML), a uniquely integrated framework designed to learn structural, attribute, and cross-modal relationships simultaneously. The proposed method stands out by combining multimodal graph encoding, dual-view contrastive learning, and fast meta-adaptation, enabling the model to rapidly identify new anomaly types with minimal labeled data. Implemented in Python using PyTorch, the model is evaluated on a multimodal smart grid dataset containing time-stamped voltage, current, power factor, frequency, temperature, and humidity measurements recorded at 15-minute intervals. Experimental results demonstrate 96.5% accuracy, 95% precision, 95.5% recall, and 95.2% F1-score, reflecting a 3–5% performance improvement over advanced baseline models due to enhanced multimodal fusion and meta-learning optimization. The study concludes that MGT-CGSSML delivers a scalable, interpretable, and real-time anomaly detection solution capable of supporting resilient and adaptive smart-grid operations, offering substantial advancements over existing methods.
Application of AI in Interior Design and its Impact 16th International Conference on Advances in Computing Control and Telecommunication Technologies Act 2025, 2025
Integration of Voice and Video Call into Android Chat Application 16th International Conference on Advances in Computing Control and Telecommunication Technologies Act 2025, 2025
Integration of Notes Generation in a Web- Based Coaching Management System 16th International Conference on Advances in Computing Control and Telecommunication Technologies Act 2025, 2025
AI-Powered Fashion Recommendation: A Deep Learning Approach to Personalized Outfit Suggestions 16th International Conference on Advances in Computing Control and Telecommunication Technologies Act 2025, 2025
Integration of Financial Data Interpretation in Expense Manager 16th International Conference on Advances in Computing Control and Telecommunication Technologies Act 2025, 2025
Inventory Management System 16th International Conference on Advances in Computing Control and Telecommunication Technologies Act 2025, 2025
Poshan: Nutrition Analysis and Dietary Tracker with CNN 16th International Conference on Advances in Computing Control and Telecommunication Technologies Act 2025, 2025
Bridal Luxe: Bridal E-Commerce: Innovations, Trends and Consumer Behavior 16th International Conference on Advances in Computing Control and Telecommunication Technologies Act 2025, 2025
A Comprehensive Review of Facial Expression, Voice Tone, and Sentiment Analysis 16th International Conference on Advances in Computing Control and Telecommunication Technologies Act 2025, 2025
A Framework for Diabetic Retinopathy Recognition Built with Deep Learning 16th International Conference on Advances in Computing Control and Telecommunication Technologies Act 2025, 2025
Enhancing the Security of Aadhaar Authentication using Post- Quantum Cryptography 16th International Conference on Advances in Computing Control and Telecommunication Technologies Act 2025, 2025
Integrating Emotion Detection for Interactive Online Learning 16th International Conference on Advances in Computing Control and Telecommunication Technologies Act 2025, 2025
UPI Fraud Detection using Machine Learning 16th International Conference on Advances in Computing Control and Telecommunication Technologies Act 2025, 2025
Personalized Movie Recommendation System using Python: A Hybrid Collaborative Filtering Approach 16th International Conference on Advances in Computing Control and Telecommunication Technologies Act 2025, 2025
WonderWise Algorithm: A Dynamic Approach to Smart Travel Planning 16th International Conference on Advances in Computing Control and Telecommunication Technologies Act 2025, 2025
ORBIT: Hybrid movie recommendation engine Dharmendra Pathak, S. Matharia, C. N. S. Murthy 2013 IEEE International Conference on Emerging Trends in Computing Communication and Nanotechnology ICE Ccn 2013, 2013
NOVA: Hybrid book recommendation engine D. Pathak, S. Matharia, C. N. S. Murthy Proceedings of the 2013 3rd IEEE International Advance Computing Conference Iacc 2013, 2013
RECENT SCHOLAR PUBLICATIONS
Optimized ship routing algorithm V Sharma, Y Parmar, A Patel, SK Mathariya, J Surana, H Pathak AIP Conference Proceedings 3441 (1), 060008 , 2026 2026
THE ROLE OF DIGITAL LITERACY IN STRENGTHENING CIVIL SERVANTS’COMPETENCIES AND PUBLIC GOVERNANCE OUTCOMES I LUKIANENKO, T NYCH, Y HREBONOZHKO, M SIKALO, L TREBYK Journal of Theoretical and Applied Information Technology 104 (6) , 2026 2026
MITIGATING MODE COLLAPSE TO IMPROVE DIVERSITY IN TEXT-TO-IMAGE GAN OUTPUTS: STRATEGIES IN ARCHITECTURAL DESIGN, TRAINING METHODOLOGIES, AND EVALUATION TECHNIQUES SK ANSARI, MALKA APPUKUTTAN, A ANOOP, SK MATHARIYA, S DV, ... Journal of Theoretical and Applied Information Technology 104 (6) , 2026 2026
Meta Learning Enhanced Graph Transformer for Robust Smart Grid Anomaly Detection. L Almahadeen, A Smerat, SK Mathariya, SR Vuda, K Ibragimova, ... International Journal of Advanced Computer Science & Applications 16 (11) , 2025 2025
Real-Time Monitoring of Fetal Arrhythmias Using AI-Driven Cardiotocography Systems Y Bhosale Vascular and Endovascular Review (ISSN: 2516-3302) , 2025 2025
Real-Time Monitoring of Fetal Arrhythmias Using AI-Driven Cardiotocography Systems. SK Mathariya, YH Bhosale, MH Rajyaguru, BP Kumar, G Umamahesh, ... Vascular and Endovascular Review 8 (1s), 278-287 , 2025 2025
Exploring GAN-Based Synthetic Medical Imaging for Improved Tumour Detection and Diagnosis S Malviya, R Pandit, P Malik, P Chouhan, SK Mathariya, J Surana Vascular and Endovascular Review 8 (1s), 189-198 , 2025 2025
An Intensive Review Identification and Classification of Eye Diseases Using Vision Transformers SK Mathariya, M Kaur, S Goyal, D Deotale, M Jain 2025 IEEE International Conference on Advances in Computing Research On … , 2025 2025
Implementation of an Integrated Framework for Blockchain Forensic Analysis Combining CAKWE, TPDT, and HLSM Techniques SK Mathariya, SP Tirumalasetty, A More, PK KG, P Kala, V Midasala 2025 World Conference on Cutting-Edge Science and Technology (WCCEST), 1-7 , 2025 2025
Support Vector Machines and Convolutional Neural Networks for Detection of Diabetic Retinopathy Hemorrhage SK Mathariya, GS Prashanth, N Thapliyal, M Jain, K Joshi, RD Sathiya 2025 World Conference on Cutting-Edge Science and Technology (WCCEST), 1-6 , 2025 2025
Precise Scene Timestamping and Content Retrieval using AI-Powered Multimodal SK Mathariya, A More, A Jawalkar, PK KG, P Rani, M Jain 2025 World Skills Conference on Universal Data Analytics and Sciences … , 2025 2025
Intelligent Reasonable Optimization for Virtual Machine Provisioning in Hybrid Cloud Using Fuzzy AHP and Cost-Effective Autoscaling KS Pokkuluri, P Sarkar, V Birchha, SK Mathariya, V Veeramachaneni, ... SN Computer Science 6 (7), 753 , 2025 2025
Generative Adversarial Network for Synthetic Data Generation SK Mathariya International Journal of Environmental Sciences 108631096 , 2025 2025 Citations: 3
Explainable Deep Temporal Modeling for Stroke Risk Assessment Using Attention-Based LSTM Networks. P Selvaperumal, FS Mary, TL Roy, YA Baker El-Ebiary, G Kalakoti, ... International Journal of Advanced Computer Science & Applications 16 (6) , 2025 2025 Citations: 1
Brain Tumor Detection in Magnetic Resonance Images Using Genetic Algorithms With Multiple Stages VP Sandeep Mathariya, Nilesh Jain, Mahaveer Jain,Ajay Vyas Proceedings of the International Conference on Recent Advancements and … , 2025 2025
Brain Tumor Detection in Magnetic Resonance Images Using Genetic Algorithms With Multiple Stages A Vyas, V Poriya, S Mathariya, N Jain, M Jain International Conference on Recent Advancements and Modernisations in … , 2025 2025
USE OF AN BGFT-DBI-LSTM AND PRFFC APPROACHES FOR ENHANCEMENT OF ONLINE DRUG RECOMMENDATION SYSTEM HS Sandeep Kumar Mathariya, Hemant Pathak, Priyanka Kumrawat, Digendra Singh ... Quality Festival 2025, 385-402 , 2025 2025
A Framework for Diabetic Retinopathy Recognition Built with Deep Learning. SR Sharma, D Mishra, A Patidar, E Patidar, M Jain, S Mathariya Grenze International Journal of Engineering & Technology (GIJET) 11 , 2025 2025
Neural Network-Based Anomaly Detection for Securing Cloud Data Transactions PN Khairnar, KR Mekala, C Nagaraj, SK Mathariya, SN Bhavanam, ... International Journal of Environmental Sciences 11 (2), 268-279 , 2025 2025
Acquiring the Ability to Identifying Covid19 using Deep CNN from Impulse Noise in Chest X-Ray Pictures MJS Mr. Sandeep Kumar Mathariya1, Mr. Mahaveer Jain*2, Dr. Piyush Chouhan3 ... INTELLIGENT SYSTEMS AND APPLICATIONS IN ENGINEERING 12 (21), 347-353 , 2024 2024
MOST CITED SCHOLAR PUBLICATIONS
NOVA: Hybrid book recommendation engine D Pathak, S Matharia, CNS Murthy 2013 3rd IEEE international advance computing conference (IACC), 977-982 , 2013 2013 Citations: 38
ORBIT: Hybrid movie recommendation engine D Pathak, S Matharia, CNS Murthy 2013 IEEE International Conference ON Emerging Trends in Computing … , 2013 2013 Citations: 24
Innovative field of cryptography: DNA cryptography ER Soni, EV Soni, ESK Mathariya International Conference on Information Technology Convergence and Services , 2012 2012 Citations: 21
A machine learning approach for early identification and prevention of Covid-19 like global pandemics SK Mathariya Int. J. Intell. Syst. Appl. Eng. , 2024 2024 Citations: 4
A data driven deep neural network model for identifying both Covid-19 disease along with potential pandemic hotspots SK Mathariya, H Shrivastava Int. J. Intell. Syst. Appl. Eng. , 2024 2024 Citations: 4
Generative Adversarial Network for Synthetic Data Generation SK Mathariya International Journal of Environmental Sciences 108631096 , 2025 2025 Citations: 3
A review on machine learning based approaches for automated detection of COVID-19 disease SK Mathariya, H Srivastava International Conference on Advanced Informatics for Computing Research, 36-49 , 2023 2023 Citations: 3
Predictive Deep Learning approach of employee attrition for imbalance datasets using SVMSMOTE algorithm with Bias Initializer S Soner, AA Hussain, R Khatri, SK Kushwaha, S Mathariya, S Bhayal 2022 Citations: 3
NOVA: Hybrid book recommendation engine. Advance Computing Conference D Pathak, S Matharia, CNS Murthy IEEE , 2013 2013 Citations: 2
Dr. CNS Mmthy Dharmendra Patliak," ORBIT: HYBRID MOVIE RECOMMENDATION ENGINE," S Matharia International Conference on Emerging Trends in Computing, Communication and … , 2013 2013 Citations: 2
Explainable Deep Temporal Modeling for Stroke Risk Assessment Using Attention-Based LSTM Networks. P Selvaperumal, FS Mary, TL Roy, YA Baker El-Ebiary, G Kalakoti, ... International Journal of Advanced Computer Science & Applications 16 (6) , 2025 2025 Citations: 1
User friendly approach for video search technique using text and image as query V Soni, SK Mathariya, R Soni 2014 Conference on IT in Business, Industry and Government (CSIBIG), 1-12 , 2014 2014 Citations: 1
Optimized ship routing algorithm V Sharma, Y Parmar, A Patel, SK Mathariya, J Surana, H Pathak AIP Conference Proceedings 3441 (1), 060008 , 2026 2026
THE ROLE OF DIGITAL LITERACY IN STRENGTHENING CIVIL SERVANTS’COMPETENCIES AND PUBLIC GOVERNANCE OUTCOMES I LUKIANENKO, T NYCH, Y HREBONOZHKO, M SIKALO, L TREBYK Journal of Theoretical and Applied Information Technology 104 (6) , 2026 2026
MITIGATING MODE COLLAPSE TO IMPROVE DIVERSITY IN TEXT-TO-IMAGE GAN OUTPUTS: STRATEGIES IN ARCHITECTURAL DESIGN, TRAINING METHODOLOGIES, AND EVALUATION TECHNIQUES SK ANSARI, MALKA APPUKUTTAN, A ANOOP, SK MATHARIYA, S DV, ... Journal of Theoretical and Applied Information Technology 104 (6) , 2026 2026
Meta Learning Enhanced Graph Transformer for Robust Smart Grid Anomaly Detection. L Almahadeen, A Smerat, SK Mathariya, SR Vuda, K Ibragimova, ... International Journal of Advanced Computer Science & Applications 16 (11) , 2025 2025
Real-Time Monitoring of Fetal Arrhythmias Using AI-Driven Cardiotocography Systems Y Bhosale Vascular and Endovascular Review (ISSN: 2516-3302) , 2025 2025
Real-Time Monitoring of Fetal Arrhythmias Using AI-Driven Cardiotocography Systems. SK Mathariya, YH Bhosale, MH Rajyaguru, BP Kumar, G Umamahesh, ... Vascular and Endovascular Review 8 (1s), 278-287 , 2025 2025
Exploring GAN-Based Synthetic Medical Imaging for Improved Tumour Detection and Diagnosis S Malviya, R Pandit, P Malik, P Chouhan, SK Mathariya, J Surana Vascular and Endovascular Review 8 (1s), 189-198 , 2025 2025
An Intensive Review Identification and Classification of Eye Diseases Using Vision Transformers SK Mathariya, M Kaur, S Goyal, D Deotale, M Jain 2025 IEEE International Conference on Advances in Computing Research On … , 2025 2025
