Recent work has shown that convolutional networks can be substantially deeper, more accurate, and efficient to train if they contain shorter connections between layers close to the input and those close to the output. In this paper, we embrace this observation and introduce the Dense Convolutional ...
MDCADNet includes a densely connected convolutional network for the feature map computation as front-end with a multi-dilated Backend Context Module (BCM)... M Singh,P Goyal - 《Expert Systems with Application》 被引量: 0发表: 2022年 Gating attention convolutional networks with dense connection...
By treating traffic data as images, both the spatial and temporal dependence of cell traffic are well captured utilizing densely connected convolutional neural networks. A parametric matrix based fusion scheme is further put forward to learn influence degrees of the spatial and temporal dependence. ...
In this paper, we developed a novel data-driven leakage detection method based on densely connected convolutional neural networks. Our method differs from conventional leakage monitoring methods by directly learning a mapping relationship between seismic data and the CO2 leakage mass. To account for ...
In the light of the fully convolutional networks (FCN) and U-Net, deep convolutional networks (DNNs) have made significant contributions in biomedical image segmentation applications. In this paper, based on U-Net, we propose MDUnet, a multi-scale densely connected U-net for biomedical image ...
Retracted: Segmentation Algorithm of Magnetic Resonance Imaging Glioma under Fully Convolutional Densely Connected Convolutional Networks SC International - 《Stem Cells International》 被引量: 0发表: 2023年 AUTOMATIC PANCREAS CT SEGMENTATION METHOD BASED ON A SALIENCY-AWARE DENSELY CONNECTED DILATED CONVOLUTI...
Skip-connected 3D DenseNet for volumetric infant brain MRI segmentation Fully convolutional neural networksDenseNetskip-connectionAutomatic 6-month infant brain tissue segmentation of magnetic resonance imaging (MRI) is still less ... TD Bui,J Shin,T Moon - 《Biomedical Signal Processing & Control》 ...
In this study, a method of scene classification for remotely sensed images based on pretrained densely connected convolutional neural networks combined with an ensemble classifier is proposed to tackle the under-utilization of local and spatial information for image classification. Specifically, we first ...
The proposed method utilizes a densely connected convolutional neural network (CNN) that is further aided by a radial location map to recover the radially dependent blurring caused by the continuous rotation of an x-ray source. The proposed method was evaluated using sparse-view data synthesized ...
Automated Segmentation of Colorectal Tumor in 3D MRI Using 3D Multiscale Densely Connected Convolutional Neural Network. 来自 NCBI 喜欢 0 阅读量: 66 摘要: The main goal of this work is to automatically segment colorectal tumors in 3D T2-weighted (T2w) MRI with reasonable accuracy. For such a...