VegetableClassifier

This research project delves into the domain of image classification, focusing on the identification of vegetables within digital images using a modified version of this dataset from kaggle

Key Techniques employed:

• Image Augmentation
• Model Architecture Exploration
• Class Imbalance handling
• Learning Rate Scheduler

Grayscale Training:

The study intentionally restricts training data to grayscale images. This was done to evaluate model performance under conditions of limited data complexity.