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---
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
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