An AI researcher developing innovative algorithms to solve real-world problems using machine learning and deep learning.
This paper presents a drone-based computer vision system using YOLOv8 for weed and disease detection in agricultural fields. The model achieved 87% precision and 80% recall for weed detection, and 60% precision and 43% recall for disease detection, demonstrating its potential for data-driven precision agriculture and crop health monitoring.
A deep learning-based change detection framework leveraging attention gates and ASPP bottlenecks to improve multi-scale feature representation and boundary localization in optical remote sensing imagery.
This work proposes an SPSA-optimized Random Forest framework to improve classification robustness and generalization for large-scale remote sensing change detection tasks.
An audio super-resolution system designed to enhance low-bandwidth speech signals for improved ASR performance, focusing on bandwidth extension and perceptual quality preservation.
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As an AI researcher, I develop intelligent systems and algorithms, with a strong focus on innovation and solving real-world challenges. I enjoy exploring new technologies and pushing the boundaries of artificial intelligence.