maab05/CustomResNet18.onnx

Custom ResNet-18 with integrated Dropout Layers

This is a custom ResNet-18 ONNX model implemented in PyTorch with integrated Dropout layers. It was trained on the CIFAR-10 dataset for image classification tasks. The model has been exported using opset version 15 and is fully compatible with the Aidge platform.

Details

• Architecture: Customized ResNet-18 with integrated Dropout layers
• Trained on: CIFAR-10 (60,000 32x32 color images, 10 classes)
• Image Preprocessing: Images were resized to 128×128
• 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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