Shiva Mehta

Synergistic Solutions: Federated Learning Meets CNNs in Soybean Disease Classification

2024

Modern agricultural demands call for creative, scalable, and flexible solutions, particularly for the early diagnosis and control of crop diseases. Using a Convolutional Neural Network (CNN) model and federated learning across five clients—O1 to O5—this …

Advanced Computational Approaches to Gun Detection with CNN-SVM Model

2024

This study tries to marry Convolutional Neural Networks (CNN) and Support Vector Machine (SVN) techniques to form a very advanced gun identification system. The system's unique feature is that it is designed to see five …

Empowering a Violence Prevention with CNN-SVM based Classification

2024

This research study comprehensively investigates the violence categorization using a hybrid Convolutional Neural Network-Support Vector Machine (CNN-SVM) model for five violence classes. We aim to create a model that can precisely and correctly discriminate between …

Advancing Tennis Analytics: A Hybrid CNN-SVM Approach for Serve Action Classification

2024

The study seeks to determine the effect of blending the eradicate CNN-SVM model on accurately identifying tennis serve shot movements. The model utilizes a large dataset of high-definition video recordings of professional tennis serves to …

Hybrid Approaches to Device-Directed Speech Detection Using Multimodal Data

2024

Device-directed speech detection (DDSD) is essential for any speech-based interface and simplifies the utilization of voice-activated systems, especially in areas with high levels of noise interference. This paper studies the enhancement of DDSD (Distributed Denial …