Deep Learning in Agriculture: MATLAB for Plant Classification

Overview

Deep learning is used in agriculture for several tasks such as quality assessment of crop and vegetation, autonomous fruit picking, and the classification and detection of different species. We will focus on classification in this webinar where we will learn to utilise the capability of a deep learning model to automate identification of flowers. From preparing the images to training and evaluating an existing deep neural network, we will explore how efficiently MATLAB handles these assignments. Besides exploring the features of deep neural network, we will deploy the newly trained model in MATLAB to classify more flower images.

Highlights

  • Prepare large sets of images to suit the Deep Learning Models
  • Start using existing deep learning models to tackle classification problems
  • Deploying the model for processing batches of images
  • Discover the features leant by deep learning model

About the Presenter

Syed Ahmad Hussain is a Training Engineer at MathWorks, specialising in the field of data processing and technical computing. He has a master’s degree in Aerospace Engineering from the University of Adelaide.

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