Results 51 to 60 of about 6,093,681 (207)

FCN-Attention: A deep learning UWB NLOS/LOS classification algorithm using fully convolution neural network with self-attention mechanism

Geo-spatial Information Science, 2023
The Ultra-Wideband (UWB) Location-Based Service is receiving more and more attention due to its high ranging accuracy and good time resolution. However, the None-Line-of-Sight (NLOS) propagation may reduce the ranging accuracy for UWB localization system in indoor environment.
Yu Pei, Ruizhi Chen, Deren Li, Xiongwu Xiao, Xingyu Zheng   +4 more
openaire   +2 more sources

LIDAR-Camera Fusion for Road Detection Using Fully Convolutional Neural Networks

, 2019
In this work, a deep learning approach has been developed to carry out road detection by fusing LIDAR point clouds and camera images. An unstructured and sparse point cloud is first projected onto the camera image plane and then upsampled to obtain a set
Svensson, Lennart, Wahde, Mattias, Svensson, Lennart,, Bellone, Mauro,, Caltagirone, Luca, Wahde, Mattias,, Bellone, Mauro, Caltagirone, Luca,   +7 more
core   +1 more source

Brain segmentation based on multi-atlas guided 3D fully convolutional network ensembles [PDF]

, 2023
In this study, we proposed and validated a multi-atlas guided 3D fully convolutional network (FCN) ensemble model (M-FCN) for segmenting brain regions of interest (ROIs) from structural magnetic resonance images (MRIs).
Tang, Xiaoying, Wu, Jiong
core   +1 more source

Noise Reduction in ECG Signals Using Fully Convolutional Denoising Autoencoders

IEEE Access, 2019
The electrocardiogram (ECG) is an efficient and noninvasive indicator for arrhythmia detection and prevention. In real-world scenarios, ECG signals are prone to be contaminated with various noises, which may lead to wrong interpretation.
Hsin-Tien Chiang, Yi-Yen Hsieh, Szu-Wei Fu, Kuo-Hsuan Hung, Yu Tsao, Shao-Yi Chien   +5 more
doaj   +1 more source

Comparison of Fully Convolutional Networks (FCN) and U-Net for Road Segmentation from High Resolution Imageries

International Journal of Environment and Geoinformatics, 2020
Segmentation is one of the most popular classification techniques which still have semantic labels. In this context, the segmentation of different objects such as cars, airplanes, ships, and buildings that are independent of background and objects such as land use and vegetation classes, which are difficult to discriminate from the background is ...
OZTURK, Ozan, SARITÜRK, Batuhan, SEKER, Dursun Zafer   +2 more
openaire   +3 more sources

Atomic Defects in Layered Transition Metal Dichalcogenides for Sustainable Energy Storage and the Intelligent Trends in Data Analytics

Advanced Science, EarlyView.
This review comprehensively summarizes the atomic defects in TMDs for their applications in sustainable energy storage devices, along with the latest progress in ML methodologies for high‐throughput TEM data analysis, offering insights on how ML‐empowered microscopy facilitates bridging structure–property correlation and inspires knowledge for precise ...
Zheng Luo, Ying Yang, Zizhen Fu, Fengqi Liu, Susu Fang, Kele Xu, Shanshan Wang   +6 more
wiley   +1 more source

Automated diabetic retinopathy grading and lesion detection based on the modified R‐FCN object‐detection algorithm

IET Computer Vision, 2020
In this work, we develop a computer‐aided retinal image screening system that can perform automated diabetic retinopathy (DR) grading and DR lesion detection in retinal fundus images.
Jialiang Wang, Jianxu Luo, Bin Liu, Rui Feng, Lina Lu, Haidong Zou   +5 more
doaj   +1 more source

Computer Vision Pipeline for Image Analysis for Freeze‐Fracture Electron Microscopy: Rosette Cellulose Synthase Complexes Case

Advanced Intelligent Discovery, EarlyView.
This paper presents a computer vision (deep learning) pipeline integrating YOLOv8 and YOLOv9 for automated detection, segmentation, and analysis of rosette cellulose synthase complexes in freeze‐fracture electron microscopy images. The study explores curated dataset expansion for model improvement and highlights pipeline accuracy, speed ...
Siri Mudunuri, Leala Carbonneau, Eric M. Roberts, Alison W. Roberts, Candace H. Haigler, Alexey V. Gulyuk, Yaroslava G. Yingling   +6 more
wiley   +1 more source

AI‐BioMech: Deep Learning Prediction of Mechanical Behavior in Aperiodic Biological Cellular Materials

Advanced Intelligent Discovery, EarlyView.
AI‐BioMech is a deep learning framework that predicts the mechanical behavior of biological cellular materials directly from 2D images. By replacing traditional finite element analysis with semantic segmentation, it identifies stress and strain distributions with 99% accuracy, offering a high‐speed, scalable alternative for analyzing complex, aperiodic
Haleema Sadia, Marcelo A. Dias, Parvez Alam   +2 more
wiley   +1 more source

FCN-VGG16 network with skip architecture.

, 2018
FCN-VGG16 network with skip architecture.
Lei Zhang (38117), Xiaoling Deng (713813), Jizhong Deng (3425030), Huasheng Huang (3425024), Yubin Lan (4722732), Aqing Yang (4722735)   +5 more
core   +1 more source