It could run on any HTML5 compliant web browser on desktop computers, internet kiosks, mobile devices, and even on smart tv.
Harumanis Web Application recognizer is trained using TensorFlow with Keras, and deployed with the help of TensorFlow.js library.
Why Convolutional Neural Network?
Common use-cases :
- as an intelligent leaf disease recognizer for web sites or web applications.
- Educational tool for students and lecturers.
- Technology preview for building smart device application which can automatically diagnose leaf disease.
- plugin or extension for web applications such as WordPress, Joomla, Google Chrome, etc.
Ray Adderley JM Gining, Mohammad Hafiz bin Ismail, and Tajul Rosli Razak, "Harumanis Mango Leaves Dataset 2021". Kaggle, 2022, doi: 10.34740/KAGGLE/DSV/3186163
Referencing this work
You can download a BibTex reference file or you may refer to this work as:
Ismail, M. H., Gining, R.A.J.M. (2022). Web Based Demo for Harumanis Leaf Disease Recognizer. Retrieved , , from: https://demo.mobilepit.com/ai/leafdisease. doi:10.5281/zenodo.6087247