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IEEE Transactions on Instrumentation and Measurement, 2020
For the safe operations of nuclear power plants, it is important to inspect the reactor internal components frequently. However, current practice involves human technicians who review the inspection videos and identify cracks on metallic surfaces of ...
Mohammad Reza Jahanshahi, Fu-Chen Chen
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For the safe operations of nuclear power plants, it is important to inspect the reactor internal components frequently. However, current practice involves human technicians who review the inspection videos and identify cracks on metallic surfaces of ...
Mohammad Reza Jahanshahi, Fu-Chen Chen
exaly +2 more sources
L-FCN: A Lightweight Fully Convolutional Network for Biomedical Semantic Segmentation
IEEE International Conference on Bioinformatics and Biomedicine, 2018For the past few years, deep learning-based methods have been widely used in the field of biomedical imaging. In biomedical image processing, the typical application of deep learning is semantic segmentation.
Kaiyue Li, G. Ding, Haitao Wang
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M-FCN: Effective Fully Convolutional Network-Based Airplane Detection Framework
IEEE Geoscience and Remote Sensing Letters, 2017Yiding Yang, Yin Zhuang, Hao Shi
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Dual-Path Adversarial Learning for Fully Convolutional Network (FCN)-Based Medical Image Segmentation [PDF]
The Visual Computer, 2018 Segmentation of regions of interest (ROIs) in medical images is an important step for image analysis in computer-aided diagnosis systems. In recent years, segmentation methods based on fully convolutional networks (FCNs) have achieved great success in ...
Lei Bi, D. Feng, Jinman Kim
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Medical Physics (Lancaster), 2022
BACKGROUND Chemical exchange saturation transfer (CEST) MRI is a promising imaging modality in ischemic stroke detection for its sensitivity in sensing post-ischemic pH alteration.
Ying-Cheng Zhao +5 more
semanticscholar +1 more source
BACKGROUND Chemical exchange saturation transfer (CEST) MRI is a promising imaging modality in ischemic stroke detection for its sensitivity in sensing post-ischemic pH alteration.
Ying-Cheng Zhao +5 more
semanticscholar +1 more source
Scene Parsing Using Fully Convolutional Network for Semantic Segmentation
Canadian Conference on Electrical and Computer Engineering, 2023When it comes to computer vision, scene parsing is a crucial part of semantic segmentation. It has a wide range of applications, including autonomous driving, robotics, gaming, natural language processing, object detection, and image and video editing ...
Nisar Ali +4 more
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Surface Defect Detection of Heat Sink Based on Lightweight Fully Convolutional Network
IEEE Transactions on Instrumentation and Measurement, 2022The surface defect detection plays an important role in industrial production and directly affects production efficiency and product quality. In this article, we focus on the surface defect detection of heat sink and propose a method based on a Ghost-SE ...
Kaifeng Yang +3 more
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Fully Convolutional Network-Based Nonlocal-Dependent Learning for Hyperspectral Image Classification
IEEE Transactions on Instrumentation and Measurement, 2022Deep convolutional neural networks play an important role in hyperspectral image (HSI) classification tasks through hierarchical learning. Recent work based on deep learning has made great progress in exploring contextual features, with more of these ...
Bing Tu +4 more
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A Part-Aware Multi-Scale Fully Convolutional Network for Pedestrian Detection
IEEE transactions on intelligent transportation systems (Print), 2021Pedestrian detection is a crucial task in intelligent transportation systems, which can be applied in autonomous vehicles and traffic scene video surveillance systems.
Peiyu Yang +5 more
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Classification for High Resolution Remote Sensing Imagery Using a Fully Convolutional Network
Remote Sensing, 2017 As a variant of Convolutional Neural Networks (CNNs) in Deep Learning, the Fully Convolutional Network (FCN) model achieved state-of-the-art performance for natural image semantic segmentation.
Gang Fu, Liu Changjun, Qijian Zhang
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