Results 41 to 50 of about 192,101 (191)

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

Multiomics Insights Into AL Amyloidosis

Medicine Bulletin, EarlyView.
ABSTRACT Light chain amyloidosis is a systemic or localized protein conformational disorder triggered by misfolded immunoglobulin light chains, leading to amyloid fibril deposition. The disease is characterized by multiorgan involvement and delayed diagnosis, contributing to poor prognosis and high mortality rates.
Zixuan Zhang, Ziru Huang, Haoxiang Tang, Xianrun Pan, Rong Wang, Dingding Zhang, Jian Huang   +6 more
wiley   +1 more source

Swin-MFINet: swin transformer based multi-feature integration network for detection of pixel-level surface defects

, 2022
Automatic surface defect detection is critical for manufacturing industries, such as steel, fabric, and marble industries. This study proposes a Swin transformer-based model called Multi-Feature Integration Network (Swin-MFINet) for pixel-level surface ...
Türkoğlu, Muammer, Hüseyin Üzen, Davut Hanbay, Üzen, Hüseyin, Muammer Türkoğlu, Berrin Yanikoglu, Yanikoglu, Berrin, Yanıkoğlu, Berrin, Hanbay, Davut   +8 more
core   +1 more source

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

Detecting Plateau Zokor (Eospalax baileyi) Mounds in UAV Imagery of Alpine Meadows Using Deep Learning Algorithms

Remote Sensing in Ecology and Conservation, EarlyView.
We developed PZM‐YOLO to automatically detect plateau zokor mounds in UAV imagery of alpine meadows. The model achieved reliable detection of small and densely distributed mounds under complex backgrounds, outperforming the baseline YOLOv5s. This framework supports mound counting, mound position, rodent impact assessment, and grassland restoration ...
Yang Yang, Limin Hua, Lianguo Wang, Jiazhen Li, Rui Dong, Siwei Yang   +5 more
wiley   +1 more source

Integrating Image Segmentation and Deep Learning to Improve Radio Frequency Propagation Models

International Journal of Satellite Communications and Networking, EarlyView.
ABSTRACT This paper proposes a multi‐sensor approach to improve radio frequency (RF) propagation models, which play a key role in the rapidly expanding field of connected vehicle technology. Focusing on the 1‐ to 20‐GHz frequency range, which is critical for both satellite‐to‐vehicle and base station‐to‐vehicle communications, our study introduces a ...
Jonathan Israel, Xavier Boulanger, Vegard Arneson   +2 more
wiley   +1 more source

Klasifikasi Detail Mobil Menggunakan Swin Transformer

, 2022
Pada penelitian ini saya menyadari bawasannya Indonesia memiliki industri manufaktur mobil terbesar kedua di Asia Tenggara dan di wilayah ASEAN (setelah Thailand yang menguasai sekitar 50 persen dari produksi mobil di wilayah ASEAN).
Wicaksono, Muhammad Alif
core  

Multi-Focus Microscopy Image Fusion Based on Swin Transformer Architecture

, 2023
In this study, we introduce the U-Swin fusion model, an effective and efficient transformer-based architecture designed for the fusion of multi-focus microscope images.
Kun Gao, Han Hank Xia, Hao Gao, Hang Shao, Wei Liu   +4 more
core   +1 more source

SWCGAN: Generative Adversarial Network Combining Swin Transformer and CNN for Remote Sensing Image Super-Resolution

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
Easy and efficient acquisition of high-resolution remote sensing images is of importance in geographic information systems. Previously, deep neural networks composed of convolutional layers have achieved impressive progress in super-resolution ...
Jingzhi Tu, Gang Mei, Zhengjing Ma, Francesco Piccialli   +3 more
doaj   +1 more source