Summer Research Intern
Conducted research on MBConvNet-CNS: A Lightweight Convolutional Neural Network (CNN) Architecture for Plant Disease Detection. The project involved designing a CNN architecture optimized for real-time plant disease detection, significantly improving efficiency and accuracy in identifying various plant diseases.Gained hands-on experience in deep learning, specifically in the development and optimization of CNN models for agricultural applications.Collaborated with a multidisciplinary team, contributing to research discussions, data analysis, and the presentation of findings.Received guidance and mentorship from leading experts, including Dr. Manas Ranjan Prusty, Dr. T. Thyagarajan, and Dr. A. Balasundaram.This internship allowed me to merge my interests in AI and agriculture, providing valuable insights into the application of cutting-edge technology in solving critical problems in the agricultural sector.