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Blood Vessels Segmentation of Hatching Eggs Based on Fully Convolutional Networks

机译:基于完全卷积网络的孵化蛋血管分割

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FCN, trained end-to-end, pixels-to-pixels, predict result of each pixel. It has been widely used for semantic segmentation. In order to realize the blood vessels segmentation of hatching eggs, a method based on FCN is proposed in this paper. The training datasets are composed of patches extracted from very few images to augment data. The network combines with lower layer and deconvolution to enables precise segmentation. The proposed method frees from the problem that training deep networks need large scale samples. Experimental results on hatching eggs demonstrate that this method can yield more accurate segmentation outputs than previous researches. It provides a convenient reference for fertility detection subsequently.
机译:FCN,训练的端到端,像素到像素,预测每个像素的结果。它已被广泛用于语义细分。为了实现孵化蛋的血管分割,本文提出了一种基于FCN的方法。训练数据集由从极小图像中提取的补丁组成,以增强数据。网络与较低层和去卷积相结合,以实现精确分割。所提出的方法从训练深网络需要大规模样本的问题中释放。孵化蛋上的实验结果表明,该方法可以产生比以前的研究更准确的分割输出。它为随后的生育检测提供了方便的参考。

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