HyperAI超神経

Retinal Oct Disease Classification On

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Acc

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このベンチマークにおける各モデルのパフォーマンス結果

モデル名
Acc
Paper TitleRepository
Joint-Attention-Network OpticNet-7199.68Improving Robustness using Joint Attention Network For Detecting Retinal Degeneration From Optical Coherence Tomography Images
Karri et al.96Optic-Net: A Novel Convolutional Neural Network for Diagnosis of Retinal Diseases from Optical Tomography Images
Lee et al.87.63Optic-Net: A Novel Convolutional Neural Network for Diagnosis of Retinal Diseases from Optical Tomography Images
MobileNet-v297.46MobileNetV2: Inverted Residuals and Linear Bottlenecks
Joint-Attention-Network ResNet50-v1100Improving Robustness using Joint Attention Network For Detecting Retinal Degeneration From Optical Coherence Tomography Images
MobileNet-v297.46Optic-Net: A Novel Convolutional Neural Network for Diagnosis of Retinal Diseases from Optical Tomography Images
Xception99.36Xception: Deep Learning With Depthwise Separable Convolutions
Lee et al.87.63Deep learning is effective for the classification of OCT images of normal versus Age-related Macular Degeneration-
ResNet50-v194.92Deep Residual Learning for Image Recognition
OpticNet-71100Optic-Net: A Novel Convolutional Neural Network for Diagnosis of Retinal Diseases from Optical Tomography Images
Joint-Attention-Network MobileNet-v299.36Improving Robustness using Joint Attention Network For Detecting Retinal Degeneration From Optical Coherence Tomography Images
Awais et al.93Optic-Net: A Novel Convolutional Neural Network for Diagnosis of Retinal Diseases from Optical Tomography Images
Xception99.36Optic-Net: A Novel Convolutional Neural Network for Diagnosis of Retinal Diseases from Optical Tomography Images
ResNet50-v194.92Optic-Net: A Novel Convolutional Neural Network for Diagnosis of Retinal Diseases from Optical Tomography Images
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