This is the machine classification model made specifically for Explora application that we developed. The model can classify and identify 30 types of plants.
For this task, we used dataset from the Kaggle user yudhaislamisulistya. This datasets consists of 30 species of plants, each species has 100 image each. The datasets itself has already been split into 3 types of data (train, test, validation), which made the classification task more convinient. Kaggle datasets can be accessed here.
EfficientNetB0 is a model in the EfficientNet family, a group of convolutional neural networks (CNNs) designed for high efficiency in terms of both accuracy and computational resource usage. EfficientNetB0 represents a significant step in developing resource-efficient yet highly accurate models, suitable for a wide range of image processing applications
Using transfer learning implementation of the EfficientNetB0 model, we achieved admirable results for the accuracy, and its loss. We believed that the model can be improved.
The classifier is made by the ML team consist of :
| Name | Bangkit ID | Github Profile |
|---|---|---|
| Ahmad Rafianto | M010BSY1438 | Github Profile |
| Muhammad Fauzi | M325BSY1522 | Github Profile |
| Immanuel Anthony Irawan | M232BSY1273 | Github Profile |
This project is licensed under the MIT License.
- A big thank you to all contributors and supporters of the project.
- Special thanks to the Bangkit Program for inspiring this initiative.
For any inquiries or collaboration proposals, please contact us at explora@example.com.