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Ken2707/
ultrasound-breast-cancer-V27

Name: ultrasound-breast-cancer-V27
Availability: InStock

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Breast Cancer Ultrasound Models Collection V2

Koleksi model untuk klasifikasi ultrasound payudara (benign, malignant, normal) dari 3 arsitektur berbeda.

📊 Model Tersedia

1. ResNet50 (TensorFlow)

File: resnet50_breast_cancer.h5 (weights asli)
Metadata: resnet50_breast_cancer.pth
Metrik: resnet50_metrics.json

2. EfficientNet (PyTorch)

File: efficientnet_breast_cancer_original.pth (weights asli)
Metadata: efficientnet_breast_cancer_original.h5
Metrik: efficientnet_metrics_original.json

3. DenseNet121 (PyTorch)

File: densenet121_breast_cancer_original.pth (weights asli)
Metadata: densenet121_breast_cancer_original.h5
Metrik: densenet121_metrics_original.json

🔧 Cara Penggunaan

ResNet50 (TensorFlow)

python

import tensorflow as tf
model = tf.keras.models.load_model('resnet50_breast_cancer.h5')
EfficientNet (PyTorch)
python
import torch
import torchvision.models as models
import torch.nn as nn

model = models.efficientnet_b7(pretrained=False)
model.classifier = nn.Linear(2560, 3)
model.load_state_dict(torch.load('efficientnet_breast_cancer_original.pth'))
model.eval()
DenseNet121 (PyTorch)
python
import torch
import torchvision.models as models
import torch.nn as nn

model = models.densenet121(pretrained=False)
model.classifier = nn.Linear(1024, 3)
model.load_state_dict(torch.load('densenet121_breast_cancer_original.pth'))
model.eval()
📁 Sumber Model
ResNet50: Kaggle Kernel

EfficientNet: Kaggle Kernel

DenseNet121: Kaggle Kernel

📝 Catatan
File .pth untuk model PyTorch berisi weights asli

File .h5 untuk model PyTorch hanya berisi metadata

Untuk ResNet50, file .h5 adalah weights asli (TensorFlow)

Ken2707/ultrasound-breast-cancer-V27