Results 31 to 40 of about 274,745 (274)
Fully automated condyle segmentation using 3D convolutional neural networks
Scientific Reports, 2022 The aim of this study was to develop an auto-segmentation algorithm for mandibular condyle using the 3D U-Net and perform a stress test to determine the optimal dataset size for achieving clinically acceptable accuracy.
Nayansi Jha +6 more
doaj +1 more source
, 2022 In neural networks, the property of being equivariant to transformations improves generalization when the corresponding symmetry is present in the data. In particular, scale-equivariant networks are suited to computer vision tasks where the same classes of objects appear at different scales, like in most semantic segmentation tasks.
Sangalli, Mateus +3 more
openaire +3 more sources
U-Net-Based Models towards Optimal MR Brain Image Segmentation
Diagnostics, 2023 Brain tumor segmentation from MRIs has always been a challenging task for radiologists, therefore, an automatic and generalized system to address this task is needed.
Rammah Yousef +6 more
doaj +1 more source
Remote Sensing, 2022 FY4A/GIIRS (Geostationary Interferometric Infrared Sounder) is the first infrared hyperspectral atmospheric vertical sounder onboard a geostationary satellite.
Shuhan Yao, Li Guan
doaj +1 more source
Seq-U-Net: A One-Dimensional Causal U-Net for Efficient Sequence Modelling [PDF]
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020 Convolutional neural networks (CNNs) with dilated filters such as the Wavenet or the Temporal Convolutional Network (TCN) have shown good results in a variety of sequence modelling tasks. While their receptive field grows exponentially with the number of layers, computing the convolutions over very long sequences of features in each layer is time and ...
Stoller, Daniel +3 more
openaire +2 more sources
Road Extraction by Deep Residual U-Net
, 2017 Road extraction from aerial images has been a hot research topic in the field of remote sensing image analysis. In this letter, a semantic segmentation neural network which combines the strengths of residual learning and U-Net is proposed for road area ...
Liu, Qingjie +2 more
core +1 more source
An attention-based U-Net for detecting deforestation within satellite sensor imagery
International Journal of Applied Earth Observations and Geoinformation, 2022 In this paper, we implement and analyse an Attention U-Net deep network for semantic segmentation using Sentinel-2 satellite sensor imagery, for the purpose of detecting deforestation within two forest biomes in South America, the Amazon Rainforest and ...
David John, Ce Zhang
doaj +1 more source
DXM‐TransFuse U-net: Dual cross-modal transformer fusion U-net for automated nerve identification
Computerized Medical Imaging and Graphics, 2022 Accurate nerve identification is critical during surgical procedures for preventing any damages to nerve tissues. Nerve injuries can lead to long-term detrimental effects for patients as well as financial overburdens. In this study, we develop a deep-learning network framework using the U-Net architecture with a Transformer block based fusion module at
Xie, Baijun +4 more
openaire +3 more sources
, 2018 Purpose: An approach for the automated segmentation of visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) in multicenter water-fat MRI scans of the abdomen was investigated, using two different neural network architectures.
Ahlström, Håkan +7 more
core +1 more source
TransClaw U-Net: Claw U-Net with Transformers for Medical Image Segmentation
, 2021 8 page, 3 ...
Chang, Yao +3 more
openaire +2 more sources