A Deep Learning Approach for Quantifying the Effects of Tuta absoluta in Tomato Plants
Date:
From July 24th to August 1st, 2020, researchers, data scientists, and practitioners from across the continent and beyond gathered virtually to explore the latest developments in data science and its applications. Among the many insightful contributions, I had the privilege to present my work titled “A Deep Learning Approach for Quantifying the Effects of Tuta absoluta in Tomato Plants” to a diverse and engaged audience in Kampala, Uganda, albeit remotely.
My talk centered on addressing the pressing issue of Tuta absoluta, a pest that poses a significant threat to tomato production, a staple food and economic crop in many countries. By leveraging deep learning, my research aimed to provide an innovative solution for quantifying the damage caused by this pest, thereby enabling more effective and targeted pest management strategies. This approach not only highlights the potential of applying AI in agriculture but also reflects a broader trend of employing data science to solve real-world problems. The virtual platform of Data Science Africa 2020 facilitated a rich exchange of ideas, allowing participants to share their research, discuss challenges, and identify opportunities for collaboration without the constraints of physical distance.