MahmoodLab

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hest-tissue-seg

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AI for Pathology Image Analysis Lab @ HMS / BWH 205

• "torch.nn.modules.flatten.Flatten",
• "segmentation_models_pytorch.encoders.timm_efficientnet.EfficientNetEncoder",
• "timm.models.efficientnet_blocks.InvertedResidual",
• "torch.nn.modules.activation.Sigmoid",
• "segmentation_models_pytorch.decoders.unet.decoder.DecoderBlock",
• "collections.OrderedDict",
• "segmentation_models_pytorch.base.modules.Activation",
• "timm.models.layers.adaptive_avgmax_pool.SelectAdaptivePool2d",
• "segmentation_models_pytorch.decoders.unet.model.Unet",
• "torch.FloatStorage",
• "torch._utils._rebuild_tensor_v2",
• "timm.models.efficientnet_blocks.SqueezeExcite",
• "torch.nn.modules.container.Sequential",
• "torch.nn.modules.conv.Conv2d",
• "torch.nn.modules.pooling.AdaptiveAvgPool2d",
• "segmentation_models_pytorch.decoders.unet.decoder.UnetDecoder",
• "segmentation_models_pytorch.base.modules.Conv2dReLU",
• "torch.LongStorage",
• "timm.models.layers.activations.Swish",
• "segmentation_models_pytorch.base.heads.SegmentationHead",
• "torch._utils._rebuild_parameter",
• "torch.nn.modules.container.ModuleList",
• "timm.models.efficientnet_blocks.DepthwiseSeparableConv",
• "torch.nn.modules.batchnorm.BatchNorm2d",
• "torch.nn.modules.linear.Identity",
• "torch.nn.modules.activation.Softmax",
• "__builtin__.set",
• "torch.nn.modules.activation.ReLU",
• "segmentation_models_pytorch.base.modules.Attention"

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