Improving Offline Gurmukhi Character Recognition: A Comparative Study of Feature Selection Techniques
This study investigates how different feature selection techniques enhance offline Gurmukhi character recognition. By analyzing various feature extraction methods and comparing their performance across machine learning models, the research identifies approaches that improve accuracy while reducing computational load. The findings support the development of more efficient and reliable OCR systems for Gurmukhi script, enabling better […]
Performance Analysis for Predicting Primary School Dropouts Using Machine Learning
This study evaluates the performance of various machine learning models in predicting primary school dropout risks by analyzing student-related data such as attendance, academic performance, and socio-economic factors. By comparing multiple algorithms, the research identifies the most effective approaches for early detection of at-risk students. The model’s predictive insights help educators implement targeted interventions, improve […]
Quantum Behaved Binary Gravitational Search Algorithm with Random Forest for Twitter Spammer Detection
This hybrid model detects Twitter spammers using quantum-inspired optimization and random forest classification. The gravitational search algorithm improves feature selection and search efficiency. Random Forest enhances decision accuracy for identifying malicious accounts. Together, they deliver a robust system for social media spam detection. For more information, click on the link below. Results in Engineering (SCI)2025https://www.sciencedirect.com/science/article/pii/S2590123025000817
Quantum-Inspired Firefly Algorithm with Ant Miner Plus for Fake News Detection
This study integrates firefly swarm intelligence with ant-based rule learning for detecting fake news. The hybrid algorithm improves classification accuracy and reduces misinformation spread. Quantum-inspired optimization enhances search efficiency within large datasets. Designed to support reliable and automated news verification systems. For more information, click on the link below. International Journal of Modern Physics C […]
Hybrid Convolutional Neural Network for Robust Attack Detection in Wireless Sensor Networks
This study presents a hybrid CNN model for detecting attacks in wireless sensor networks. The system analyzes sensor data patterns to identify abnormal or malicious activity. Its deep-learning approach improves accuracy and robustness in threat detection. Designed to strengthen security in distributed IoT and sensor-based environments. For more information, click on the link below. Internet […]