Multi-Class Deep Learning Model for AIR Lab iBeans Using TensorFlow Take 1

Template Credit: Adapted from a template made available by Dr. Jason Brownlee of Machine Learning Mastery.

SUMMARY: The purpose of this project is to construct a predictive model using various machine learning algorithms and to document the end-to-end steps using a template. The AIR Lab iBeans dataset is a multi-class classification situation where we are trying to predict one of several (more than two) possible outcomes.

INTRODUCTION: This dataset is of leaf images taken in the field in different districts in Uganda by the Makerere AI lab in collaboration with the National Crops Resources Research Institute (NaCRRI), Uganda’s national body in charge of agriculture research.

The goal is to build a robust machine learning model that can distinguish between diseases in the Bean plants. The data is of leaf images representing three classes: the healthy images and two disease classes, including Angular Leaf Spot and Bean Rust diseases. The model should be able to distinguish between these three classes with high accuracy. The end goal is to build a model that can be deployed on a mobile device and used in the field by a farmer.

In this Take1 iteration, we will construct and tune machine learning models for this dataset using TensorFlow with a simple VGG-5 network. We will observe the best result that we can obtain using the validation and test datasets. The final output from this iteration will become our baseline performance level for future iterations.

ANALYSIS: From iteration Take1, the performance of the baseline model achieved an accuracy score of 75.94% on the validation dataset after 50 epochs. Furthermore, the same baseline processed the test dataset with an accuracy score of 82.03%.

CONCLUSION: For this dataset, the model built using TensorFlow with VGG-5 blocks performed adequately with the image datasets. However, we should consider tuning the model further by using image augmentation and regularization techniques.

Dataset Used: AIR Lab iBeans Dataset

Dataset ML Model: Multi-classification with numerical attributes

Dataset Reference:

The HTML formatted report can be found here on GitHub.