Results 21 to 30 of about 1,457,471 (199)

STHarDNet: Swin Transformer with HarDNet for MRI Segmentation

Applied Sciences, 2022
In magnetic resonance imaging (MRI) segmentation, conventional approaches utilize U-Net models with encoder–decoder structures, segmentation models using vision transformers, or models that combine a vision transformer with an encoder–decoder model ...
Yeonghyeon Gu, Zhegao Piao, Seong Joon Yoo   +2 more
doaj   +1 more source

LAVT: Language-Aware Vision Transformer for referring image segmentation [PDF]

, 2022
Referring image segmentation is a fundamental vision-language task that aims to segment out an object referred to by a natural language expression from an image.
Zhao, H, Yang, Z, Yang, Zhao, Torr, Philip H.S., Tang, Y, Torr, P, Wang, J, Chen, K, Chen, Kai, Torr, Philip, Zhao, Hengshuang, Wang, Jiaqi, Tang, Yansong   +12 more
core   +1 more source

Diverse features discovery transformer for pedestrian attribute recognition [PDF]

, 2023
Recently, Swin Transformer has been widely explored as a general backbone for computer vision, which helps to improve the performance of vision tasks due to the ability to establish associations for long-range dependencies of different spatial locations.
Hussain, Amir, Zheng, Aihua, Wang, Huimin, He, Ran, Wang, Jiaxiang, Huang, Huaibo   +5 more
core   +1 more source

Convolutional Neural Networks or Vision Transformers: Who Will Win the Race for Action Recognitions in Visual Data?

Sensors, 2023
Understanding actions in videos remains a significant challenge in computer vision, which has been the subject of several pieces of research in the last decades.
Oumaima Moutik, Hiba Sekkat, Smail Tigani, Abdellah Chehri, Rachid Saadane, Taha Ait Tchakoucht, Anand Paul   +6 more
doaj   +1 more source

Pre-breakdown Characteristics of Contaminated Power Transformer Oil [PDF]

, 2007
In this paper we have studied pre-breakdown characteristics of transformer oil in the presence of different levels of contamination. The contaminant is fibrous dust from pressboard insulation used for high voltage transformers.
Zuber, H M, Chen, G
core   +2 more sources

Transformer-based ripeness segmentation for tomatoes

Smart Agricultural Technology, 2023
With the recent development of computer vision technology, various computer vision techniques have been applied to agriculture. Recently, the Transformer network has been introduced to image recognition, which allows a different approach to extracting ...
Risa Shinoda, Hirokatsu Kataoka, Kensho Hara, Ryozo Noguchi   +3 more
doaj   +1 more source

Transformer architectures for computer vision: A comprehensive review and future research directions [PDF]

EPJ Web of Conferences
Long-range dependencies and contextual relationships in videos were captured by using Convolutional Neural Networks (CNNs) in past. Recently the use of Transformers is started for capturing the long-range dependencies and contextual relationships in ...
Ugile Tukaram, Uke Nilesh
doaj   +1 more source

eolphd/transformer-forecasting: transformer-forecasting

, 2023
<p>Main code and modules of a transformer neural network for environmental time series forecasting, including input data used for test. Orozco-López and Kaplan "Interpretable Transformer Neural Network Prediction of Diverse Environmental Time ...
eolphd
core   +1 more source

Computational and experimental verification of the equivalent permeability of the step-lap joints of transformer cores

, 2008
The paper develops an efficient computational method for establishing equivalent characteristics of magnetic joints of transformer cores, with special emphasis on step-lap design.
N. Nihat, E. Napieralska-Juszczak, Sykulski, J. K., Napieralska-Juszczak, E., J.K. Sykulski, J.Ph. Lecointe, Lecointe, J. Ph., Nihat, N.   +7 more
core   +2 more sources

Supervised deep learning with vision transformer predicts delirium using limited lead EEG

Scientific Reports, 2023
As many as 80% of critically ill patients develop delirium increasing the need for institutionalization and higher morbidity and mortality. Clinicians detect less than 40% of delirium when using a validated screening tool.
Malissa A. Mulkey, Huyunting Huang, Thomas Albanese, Sunghan Kim, Baijian Yang   +4 more
doaj   +1 more source