Machine Learning Intern

• Jul 2023 - Present

AI-Driven ToBRFv Detection from Farm Video Scans 🌱🔍 📅 Duration: 2 Months During an enriching 2-month internship, I spearheaded a groundbreaking project aimed at revolutionizing the agriculture industry. Harnessing the power of Artificial Intelligence and cutting-edge technologies, I developed a robust machine learning model with the ability to detect Tomato Brown Rugose Fruit Virus (ToBRFv) from video scans captured on farms. 🔬 Project Highlights: 🌾 Innovative Detection: Employing state-of-the-art object detection models, I crafted an intelligent system capable of identifying ToBRFv-infected plants in vast farm landscapes. This solution not only expedites disease identification but also enhances yield prediction. 🎯 Precision Segmentation: Leveraging advanced segmentation models, including 'Segment Anything' by Meta, I fine-tuned the model to precisely outline and isolate affected areas. This segmentation capability allows for targeted treatment and resource optimization. 🔗 Interdisciplinary Collaboration: Throughout the project, I collaborated with agronomists, data scientists, and domain experts to ensure the model's accuracy and practicality in real-world scenarios. The cross-disciplinary exchange of knowledge fostered innovative problem-solving and enriched my understanding of agricultural challenges. 📈 Results and Impact: My internship culminated in the creation of an AI-driven solution poised to revolutionize disease management in agriculture. By swiftly identifying and segmenting ToBRFv-infected plants, this model contributes to early intervention, minimizing crop losses, and promoting sustainable farming practices. Show less