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Two-Stage Deep Learning Model for Automated Segmentation ... - NCBI
www.ncbi.nlm.nih.gov › PMC9688308
Nov 8, 2022 · A deep learning model was developed to automatically segment and classify splenomegaly in patients with malignant lymphoma versus patients with cirrhotic ...
Missing: Modular | Show results with:Modular
Dec 15, 2021 · In this present paper, we are considering the modular neural network architecture with two phase learning for pattern classification of ...
In this paper, we propose a novel two-stage ensemble method based on deep convolutional neural networks. In the first stage, we perform the image segmentation, ...
The main novelty of this algorithm is the aggregation of the low-resolution result from stage 1 with the high-resolution patches from stage 2, and the U-Net ...
Jul 22, 2022 · This paper proposes a design method for a modular convolutional neural network model which solves the problem of over-fitting and large model parameters
Dec 30, 2021 · In this paper, a new method utilising a two-stage convolutional neural network (CNN) is proposed for road crack detection and segmentation in images at the ...
Missing: Modular | Show results with:Modular
The first CNN identifies the vessel region and the output of this net is used by a second CNN to identify and segment the contents of the object (Figure 1).
In this task, we propose methods combining Residual module, Inception module, Adaptive Convolutional neural network with ... [Show full abstract] U-Net ...
Oct 14, 2017 · This work examines a method for serially connecting convolutional neural networks for semantic segmentation of materials inside transparent vessels.
Missing: Two- Stage
Referring Image Segmentation (RIS) aims at segmenting the target object from an image referred by one given natural language expression.