Plant-Seedling-Image-Classification

Objective: Build a CNN classifier that will be able to accurately predict the species of plant seedling based on an image of that seedling taken from the top.
Outcome: Pre-processed and reshaped images and labels to be used in a CNN, using techniques like gaussian blurring and normalization. Fit and trained a model that achieved an 80-90% accuracy in correctly identifying plant species, and produced a multi-class confusion matrix with details on the model’s performance.