Keras model for wildfire or nowildfire classification. The model gets in input a dataset as numpy arrays (dimension 100x100x3) and returns the predicted labels.
Performance
Accuracy score: 0.9505 (validation). Running time: 2 min for 23 training epochs with early stopping (total number of epochs: 50) on a gpu Nvidia a100. Modified hyperparameters: Input shape: (100,100,3); Optimizer: 'adam'; batch size: 128. Train-test-valid split: 70-15-15. Loss function: sparse_categorical_crossentropy.
Use case
common
Name of resource
LeNet Classifier
ID
lenet_classifier
Description
Multi-layer Convolutional Neural Network for image classification
Main category
Deep Learning
Other category
No response
Publication date
2023-04-04
Objective
classification
Platform
Google Colab
Framework
Keras
Architecture
CNN - Convolutional-Neural-Network
Approach
supervised
Algorithm
LeNet
Processor
gpu
OS
linux
Keyword
classification, CNN, LeNet
Reference link
https://en.wikipedia.org/wiki/LeNet
Example
https://github.com/cozzolinoac11/wildfire_prediction/blob/main/ann.ipynb
Input data used
Characteristics of input data
Biases and ethical aspects
No response
Output data obtained
Characteristics of output data
Performance
Accuracy score: 0.9505 (validation). Running time: 2 min for 23 training epochs with early stopping (total number of epochs: 50) on a gpu Nvidia a100. Modified hyperparameters: Input shape: (100,100,3); Optimizer: 'adam'; batch size: 128. Train-test-valid split: 70-15-15. Loss function: sparse_categorical_crossentropy.
Conditions for access and use
cc-by-4.0
Constraints
No response