To address this problem, we propose a new 3D Cross-Pseudo Supervision (3D-CPS) method, a semi-supervised network architecture based on nnU-Net with the Cross-Pseudo Supervision method. We design a new nnU-Net based preprocessing. In addition, we set the semi-supervised loss weights to ...
CVPR 2021|June 2021 In this paper, we study the semi-supervised semantic segmentation problem via exploring both labeled data and extra unlabeled data. We propose a novel consistency regularization approach, called cross pseudo supervision (CPS). Our approach imposes the consistency on...
We propose a novel consistency regularization approach, called cross pseudo supervision (CPS). Our approach imposes the consistency on two segmentation networks perturbed with different initialization for the same input image. The pseudo one-hot label map, output from one perturbed segmentation network,...
[CVPR 2021] CPS: Semi-Supervised Semantic Segmentation with Cross Pseudo Supervision - charlesCXK/TorchSemiSeg
(a) The supervised segmentation loss (ℓseg) is computed on the labeled samples using the ground truth (GT) and the network outputs. (b) For the unlabeled images, the pseudo-supervision loss (ℓps) is computed using the pseudo labels (pl) generated from ensemble of predictions on the ...
To address this issue, we propose a class-aware cross pseudo supervision (C 2 ^2 PS) framework, which built upon cross pseudo supervision (CPS) method. Specifically, Our approach enhances network learning for small organs in unlabeled data through a dynamic threshold-based consistency (DTC) ...
FA+CPS: By further employing cross-pseudo-supervision to train the network, the overall feature alignment is enforced and the consistency of the network’s output is constrained. In this way, combining the images generated by the feature alignment sub-network with CPS for network training improved...
To address this, we introduce an innovative semi-supervised learning framework based on cross-pseudo supervision (CPS) and contrastive learning, termed Semi-supervised Polyp Segmentation (SemiPolypSeg), which requires only limited labeled data. First, a new segmentation architecture, the Hybrid ...
The methods include cross-linking of linear PVA chains with glyoxal, glutaraldehyde, or borate and preparation of semicrystalline gels by freezing and thawing of aqueous PVA solutions that allows for network structures cross-linked with pseudo-permanent crystallites. The freezing method is regarded as ...
which appear as pseudo pore sizes when identified with convenient techniques. The traditional method of producing xerogels, aerogels or cryogels and their activated carbons that is reported in the literature includes specific steps. These steps include the (i) synthesis process, in which the gelation...