Jun 19, 2019 · The digital image segmentation algorithm based on deep learning plays an important role in the monitoring of seabed mineral resources.
An improved segmentation algorithm by learning a deep convolution network is proposed, which shows a better segmentation result on the seabed mineral image ...
For this reason, an improved segmentation algorithm by learning a deep convolution network is proposed. A typical encoder-decoder structure is used to construct ...
Jun 10, 2019 · The digital image segmentation algorithm based on deep learning plays an important role in the monitoring of seabed mineral resources.
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In this paper, an improved mineral image segmentation is proposed based on the modified U-Net. The pyramid upsampling module and residual module are bring into ...
In this paper, the existing deep-sea nodule mineral image segmentation algorithms are studied in depth and divided into traditional and deep learning-based ...
UPSNet: A Unified Panoptic Segmentation Network; An Improved U-Net Convolutional Networks for Seabed Mineral Image Segmentation. DeepLab based Models. 2017.
May 18, 2015 · In this paper, we present a network and training strategy that relies on the strong use of data augmentation to use the available annotated samples more ...
Missing: Improved Seabed Mineral
May 16, 2022 · The evaluation index shows that the Pix2PixHD algorithm effectively improves the accuracy rate and the recall rate of deep-sea mineral image ...
In this paper, an improved mineral image segmentation is proposed based on the modified U-Net. ... convolutional neural network on the underwater mineral image ...
Missing: Seabed | Show results with:Seabed