该研究通过建立基于OCT图像的敏感结构引导的深度学习预测模型(SSG-Net),实现了对nAMD抗VEGF治疗后短期解剖与视功能改变的双元预测。 湿性年龄相关性黄斑变性(nAMD)是老年人群出现不可逆性视力丧失的主要原因之一,以黄斑区出现脉络膜新生血管(CNV)为特征,常合并反复发作的视网膜下积液、出血等改变,最终导致视网膜下瘢痕...
To address the need for efficient and accurate fault diagnosis in scroll compressor technology under varying operating states, diverse failure modes, and different operating conditions, a multi-branch convolutional neural network fault diagnosis method (SSG-Net) has been developed. This method is based...
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SSGNet.We propose a Scene Structure Guidance Network, SSGNet, a single general neural network architecture for extracting task-specific structural features of scenes.. Python >= 3.6 PyTorch >= 1.0 NVIDIA GPU + CUDA cuDNN Getting Started
cd ./SSGNet python train.py Test SSGNetYou should change SSGNET/options/test_options --ssgnet-pretrained : path to your pretrained SSGNet --save_result : path to save SSGNet outputpython test.py Train DenoisingYou should change Denoising/options/train_options --dataset_root : path to...
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A straightforward implementation of FNV-1a hash algorithm for .NET. Usage is very simple. For instance to calculate 32-bit FNV-1a hash of ASCII string "some string": var buffer = Encoding.UTF8.GetBytes("some string"); uint result = Fnv1a.Hash32(buffer); // 32-bit hash ulong result...
Then, we propose a novel hybrid learning-based network, named SSGAM-Net, which consists of the GAM module and Encoder–Decoder module. It is an elegant pipeline, with no need for redundant pre-processing or post-processing. Due to the lack of airborne true-color point cloud datasets, we ...
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