Volume 12, Number 1

Application of Convolutional Neural Network In LAWN Measurement


J. Wilkins1, M. V. Nguyen1, B. Rahmani1, 2, 1Fontbonne University, USA, 2Maryville University, USA


Lawn area measurement is an application of image processing and deep learning. Researchers used hierarchical networks, segmented images, and other methods to measure the lawn area. Methods’ effectiveness and accuracy varies. In this project, deep learning method, specifically Convolutional neural network, was applied to measure the lawn area. We used Keras and TensorFlow in Python to develop a model that was trained on the dataset of houses then tuned the parameters with GridSearchCV in ScikitLearn (a machine learning library in Python) to estimate the lawn area. Convolutional neural network or shortly CNN shows high accuracy (94 -97%). We may conclude that deep learning method, especially CNN, could be a good method with a high state-of-art accuracy.


Lawn Measurement, Convolutional Neural Network, Keras, TensorFlow, Scikit-Learn.