Results 61 to 70 of about 206,029 (232)

ViTAMIn‐O: Democratizing Computer Vision‐Based Machine Learning for Stem Cell Research

Advanced Intelligent Systems, EarlyView.
This study introduces a fully open generalist computer vision model for predicting the differentiation outcomes of stem cell‐based model systems, together with its code‐free deployment platform, ColabViTAMIn‐O. It is benchmarked against various architectures, datasets, and training protocols.
Ferhat Hamurcu, Markus Breunig, Arpad Varga, Bianka Bosch, Jessica Lindenmayer, Anjan T. Kanakappady, Kevin Achberger, Natalia Pashkovskaia, Alexander Kleger, Stefan Liebau, Stefanie Klingenstein, Moritz Klingenstein   +11 more
wiley   +1 more source

DarSwin: Distortion Aware Radial Swin Transformer

2023 IEEE/CVF International Conference on Computer Vision (ICCV), 2023
18 pages, 12 ...
Akshaya Athwale, Arman Afrasiyabi, Justin Lagüe, Ichrak Shili, Ola Ahmad, Jean-François Lalonde   +5 more
openaire   +2 more sources

AI‐Powered 3D Liver Fat Volumetric Map for Clinical‐Grade Steatosis Assessment From Cross‐Modality MRI

Advanced Intelligent Systems, EarlyView.
An automated, AI‐powered system generates a 3D liver fat volumetric map for precise fat fraction quantification from MRI. By overcoming manual analysis constraints, it provides high‐fidelity spatial characterization of steatosis. This graphical abstract highlights a clinically robust framework that enables efficient, anatomically informed assessment ...
Bincan Deng, Yingyun Gong, Xiao Wang, Xinxi Wang, Dingding Chen, Chen Xuan, Qing Xu, Hongwen Zhou, Yuwen Cui, Manuel Doblare   +9 more
wiley   +1 more source

Leveraging Big Multitemporal Multisource Satellite Data and Artificial Intelligence for the Detection of Complex and Invisible Features: The Case of Extensive Irrigation Mapping

Archaeological Prospection, EarlyView.
ABSTRACT The detection of buried or obscured archaeological features remains a central challenge in landscape archaeology, particularly in the irrigated floodplains of Mesopotamia where levees and canals formed the basis of complex agrarian systems. This study presents a deep learning–based approach for the large‐scale, automated detection of ancient ...
Nazarij Buławka, Hector A. Orengo, Felipe Lumbreras Ruiz, Iban Berganzo‐Besga, Ekta Gupta   +4 more
wiley   +1 more source

Usability of a deep learning platform for detecting radiographic bone loss and furcation involvement

Journal of Periodontology, EarlyView.
Abstract Background Assessing radiographic bone condition is important for periodontal diagnosis. The accuracy of radiographic interpretation depends highly on a clinician's experience and knowledge. This study aimed to develop a deep learning‐based online platform that aids clinicians in diagnosing periodontitis based on periapical radiographs and to ...
Chun‐Teh Lee, Tanjida Kabir, Alaa Alsaffar, Jiman Nelson, Sally Sheng, Hsiu‐Wan Meng, Mohammad Qali, Muhammad F. Walji, Xiaoqian Jiang, Shayan Shams   +9 more
wiley   +1 more source

Swin-transformer for weak feature matching

Scientific Reports
Feature matching in computer vision is crucial but challenging in weakly textured scenes due to the lack of pattern repetition. We introduce the SwinMatcher feature matching method, aimed at addressing the issues of low matching quantity and poor matching precision in weakly textured scenes.
Yuan Guo, Wenpeng Li, Ping Zhai
openaire   +3 more sources

Deep‐DSP2: Cross‐Domain Deep Learning Direct MR Signal Prediction for RF Shielding‐Free MRI

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose To develop a deep learning approach to electromagnetic interference (EMI) elimination in the presence of dynamically varying electromagnetic coupling relationships (i.e., spectral domain transfer functions) between MRI receive and EMI sensing coils for RF shielding‐free ultra‐low‐field (ULF) MRI.
Jiahao Hu, Yujiao Zhao, Alex T. L. Leong, Ed X. Wu   +3 more
wiley   +1 more source

Fine-Grained Ship Classification by Combining CNN and Swin Transformer

, 2022
The mainstream algorithms used for ship classification and detection can be improved based on convolutional neural networks (CNNs). By analyzing the characteristics of ship images, we found that the difficulty in ship image classification lies in ...
Yalun Zhang, Qingxia Xu, Liang Huang, Fengxiang Wang   +3 more
core   +1 more source

An Inline‐Integrable Image Restoration Model With ROI Fine‐Tuning and Slice‐to‐Volume Reconstruction for Accelerated Whole‐Brain Vessel Wall Imaging

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose To develop a vessel wall imaging (VWI)‐dedicated image restoration model enabling high‐resolution whole‐brain VWI in under 6 min. Methods A transformer‐based 2.5D model was trained in a supervised manner to enhance the image quality of CAIPIRINHA 2 × 2‐accelerated VWI acquisitions to a level comparable to that of GRAPPA twofold ...
Pengcheng Wang, Jingxiang Zhang, Jiayu Xiao, Junzhou Chen, Zhenjia Wang, Jin Li, Qingle Kong, Steven Y. Cen, Sophia X. Cui, Yifei Zhang, Wei Yu, Qi Yang, Nasim Sheikh‐Bahaei, William J. Mack, Zhaoyang Fan   +14 more
wiley   +1 more source

Network structure of Swin-Transformer-YOLOv5.

An essential industrial application is the examination of surface flaws in hot-rolled steel strips. While automatic visual inspection tools must meet strict real-time performance criteria for inspecting hot-rolled steel strips, their capabilities are ...
Haoyue Huang (3450605), Qiuyan Wang (237527), Haibing Dong (17846963)   +2 more
core   +1 more source