In this paper, we propose a novel Low-cost U-Net (LCU-Net) for the Environmental Microorganism (EM) image segmentation task to assist microbiologists in detecting and identifying EMs more effectively. The LCU-Net is an improved Convolutional Neural Network (CNN) based on U-Net, Inception, and concatenate operations. It addresses the limitation of single receptive field setting and the relatively high memory cost of U-Net. Experimental results show the effectiveness and potential of the proposed LCU-Net in the practical EM image segmentation field. (c) 2021 Elsevier Ltd. All rights reserved
With fast-growing computing power and large amounts of data availability, deep learning (DL) algorit...
In biomedical research, detailed structure of tissues, cells, organelles and macromolecular complexe...
For the past few years, Convolutional Neural Networks have had tremendous impact not only within the...
In this paper, we propose a novel Low-cost U-Net (LCU-Net) for the Environmental Microorganism (EM) ...
In this paper, we propose a novel Low-cost U-Net (LCU-Net) for the Environmental Microorganism (EM) ...
Abstract: The microscopic images of wastewater bacteria are analysed, and a scheme for classificatio...
Object segmentation and structure localization are important steps in automated image analysis pipel...
U-Net is the most cited and widely-used deep learning model for biomedical image segmentation. In th...
Due to massive expansion of the mass spectrometry and constant price growth of the human labour the ...
Scientists are on the lookout for a practical model that can serve as a standard for sorting out, id...
When pharmaceutical companies develop new drugs or vaccines there are large amounts of data in the f...
This survey is aimed to release different methods of biological image segmentation via computer proc...
In recent years, medical image segmentation using deep learning methods has become more and more pop...
This work deals with the use of a convolutional neural network in the area of segmentation of images...
ABSTRACTThe human gut microbiome is associated with a large number of disease etiologies. As such, i...
With fast-growing computing power and large amounts of data availability, deep learning (DL) algorit...
In biomedical research, detailed structure of tissues, cells, organelles and macromolecular complexe...
For the past few years, Convolutional Neural Networks have had tremendous impact not only within the...
In this paper, we propose a novel Low-cost U-Net (LCU-Net) for the Environmental Microorganism (EM) ...
In this paper, we propose a novel Low-cost U-Net (LCU-Net) for the Environmental Microorganism (EM) ...
Abstract: The microscopic images of wastewater bacteria are analysed, and a scheme for classificatio...
Object segmentation and structure localization are important steps in automated image analysis pipel...
U-Net is the most cited and widely-used deep learning model for biomedical image segmentation. In th...
Due to massive expansion of the mass spectrometry and constant price growth of the human labour the ...
Scientists are on the lookout for a practical model that can serve as a standard for sorting out, id...
When pharmaceutical companies develop new drugs or vaccines there are large amounts of data in the f...
This survey is aimed to release different methods of biological image segmentation via computer proc...
In recent years, medical image segmentation using deep learning methods has become more and more pop...
This work deals with the use of a convolutional neural network in the area of segmentation of images...
ABSTRACTThe human gut microbiome is associated with a large number of disease etiologies. As such, i...
With fast-growing computing power and large amounts of data availability, deep learning (DL) algorit...
In biomedical research, detailed structure of tissues, cells, organelles and macromolecular complexe...
For the past few years, Convolutional Neural Networks have had tremendous impact not only within the...