A Deep Learning Approach for Determining Effects of Tuta Absoluta in Tomato Plants
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In the midst of the global shift towards virtual events due to the COVID-19 pandemic, I had the distinct opportunity to present my research at the Computer Vision for Agriculture workshop. This event was part of the larger International Conference on Learning Representations (ICLR), hosted virtually from April 26th to 30th, 2020 in Addis Ababa, Ethiopia. My presentation, entitled “A Deep Learning Approach for Determining Effects of Tuta Absoluta in Tomato Plants,” focused on leveraging advanced AI techniques to tackle the challenges posed by Tuta absoluta, a pest that significantly impacts tomato crops. The innovative approach highlighted in my research emphasized the potential of deep learning in enhancing agricultural pest detection and management.
The significance of this work was further recognized through its publication in the conference proceedings. This acknowledgment not only validated the research but also contributed to the growing body of knowledge in the field of AI in agriculture. The publication serves as a testament to the potential of AI in addressing real-world problems and enhancing agricultural practices.
The virtual format of the workshop, necessitated by the ongoing pandemic, created an unprecedented opportunity for a broader, more diverse audience to engage and collaborate. It allowed experts and enthusiasts from various parts of the world to participate and share insights, fostering a rich environment of global collaboration.