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NET Activity Report: March-December 1983

open access: yes, 1983
MARTONE, Raffaele, in NET Team
core  

E-Res U-Net: An improved U-Net model for segmentation of muscle images

Expert Systems with Applications, 2021
Abstract In this paper, we propose a new semantic segmentation network called ’E-Res U-Net’, to achieve better segmentation results of deep and superficial muscles in ultrasonic muscle images. This model is based on U-Net, and its structure has been modified to improve the performance of the algorithm.
Junsheng Zhou   +4 more
openaire   +1 more source

Improved segmentation by adversarial u-net

Medical Imaging 2021: Computer-Aided Diagnosis, 2021
Medical image segmentation has a fundamental role in many computer-aided diagnosis (CAD) applications. Accurate segmentation of medical images is a key step in tracking changes over time, contouring during radiotherapy planning, and more. One of the state-of-the-art models for medical image segmentation is the U–Net that consists of an encoder-decoder ...
David Sriker   +3 more
openaire   +1 more source

Information Flow Through U-Nets

2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), 2021
Deep Neural Networks (DNNs) have become ubiquitous in medical image processing and analysis. Among them, U-Nets are very popular in various image segmentation tasks. Yet, little is known about how information flows through these networks and whether they are indeed properly designed for the tasks they are being proposed for.
Suemin Lee, Ivan V. Bajic
openaire   +1 more source

MVP U-Net: Multi-View Pointwise U-Net for Brain Tumor Segmentation

2021
It is a challenging task to segment brain tumors from multi-modality MRI scans. How to segment and reconstruct brain tumors more accurately and faster remains an open question. The key is to effectively model spatial-temporal information that resides in the input volumetric data.
Changchen Zhao   +3 more
openaire   +2 more sources

A variational U‐Net for motion retargeting

Computer Animation and Virtual Worlds, 2020
AbstractMotion retargeting is the process of copying motion from one character (source) to another (target) when the source and target body sizes and proportions (of arms, legs, torso, etc.) are different. The problem of automatic motion retargeting has been studied for several decades; however, the motion quality obtained with the application of ...
Seong Uk Kim   +2 more
openaire   +2 more sources

A variational U-Net for motion retargeting

SIGGRAPH Asia 2018 Posters, 2018
In this paper, we present a novel motion retargeting system by using the deep autoencoder combining the Deep Convolution Inverse Graphics Network (DC-IGN) ([Kulkarni et al. 2015]) and the U-Net ([Long et al. 2015]) to produce high-quality human motion. The retargeted motion is fully-automatically and naturally generated from the given input motion and ...
Hanyoung Jang   +4 more
openaire   +2 more sources

Application of U-Net

2020
Lung cancer (lung carcinoma) is a malignant tumor defined by unrestrained cell growth in lung tissues. Long-term tobacco smoking is the major cause of lung cancer. Radiographs and Computed Tomography (CT) are used to see the lung cancer. The diagnosis is performed by the process called bronchoscopy and can be confirmed by biopsy. CT is a lung screening
Sathishkumar, R.   +2 more
openaire   +1 more source

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