metadata
license: cc
tags:
- onnx
- image-classification
- cifar10
- dropout
- aidge
pipeline_tag: image-classification
datasets:
- cifar10
metrics:
- type: accuracy
value: 69.96%
model-index:
- name: Custom ResNet-18 with Integrated Dropout
results:
- task:
type: image-classification
name: Image Classification
dataset:
name: CIFAR-10
type: cifar10
metrics:
- type: accuracy
value: 69.96%
MarwaNet (ONNX)
This is a custom convolutional neural network (CNN) trained on the CIFAR-10 dataset, developed to test the integration of a custom Dropout operator for the Aidge platform.
Details
- Architecture: Custom Convolutional Neural Network (CNN) with a Dropout layer
- Trained on: CIFAR-10 (60,000 32x32 color images, 10 classes)
- Data Normalization:
mean = [0.4914, 0.4822, 0.4465];std = [0.2023, 0.1994, 0.2010] - Dropout Probability: 0.3
- ONNX opset version: 15
- Conversion tool: PyTorch → ONNX