Innovation Owner
Mr. SIRAWIT KHUTBUA
Student
Details
This project develops an AI model using Deep Learning to classify coral health into four categories: Healthy, Bleached, Pale, and Dead. By employing 5-fold Cross-Validation, the model provides efficient and accurate analysis to support marine ecosystem conservation.
Currently, climate change and human activities are causing rapid deterioration of coral reefs worldwide. Monitoring coral health is essential for marine ecosystem conservation. This project focuses on developing an Artificial Intelligence (AI) model to classify coral health into four categories:
- Healthy
- Bleached
- Pale
- Dead
Using Deep Learning techniques with pre-trained convolutional neural network (CNN) for image classification. To improve accuracy and mitigate overfitting, 5-fold Cross-Validation is employed during training, and the best-performing model is saved. The results of this project can be applied to monitor coral reef conditions and assist marine scientists in analyzing coral health more efficiently and accurately. This contributes to better conservation planning for marine ecosystems in the future.
Objective
The objectives include developing an AI model to classify coral health into four categories, enhancing model accuracy via 5-fold Cross-Validation, and supporting the monitoring of coral reef changes through advanced technology.
- Develop an Artificial Intelligence (AI) model to classify coral health into four categories: Healthy, Bleached, Pale, and Dead.
- Improve model accuracy using 5-fold Cross-Validation and save the best-performing model.
- Support the analysis and monitoring of coral reef changes using artificial intelligence technology.