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Optimal CNN-based semantic segmentation model of cutting slope images

Mansheng LIN; Shuai TENG; Gongfa CHEN; Jianbing LV; Zhongyu HAO

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 4,   Pages 414-433 doi: 10.1007/s11709-021-0797-6

Abstract: This paper utilizes three popular semantic segmentation networks, specifically DeepLab v3+, fully convolutionalThis paper also analyzes the segmentation strategies of the three networks in terms of feature map visualization

Keywords： slope damage     image recognition     semantic segmentation     feature map     visualizations    

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Fast detection algorithm for cracks on tunnel linings based on deep semantic segmentation

Frontiers of Structural and Civil Engineering 2023, Volume 17, Issue 5,   Pages 732-744 doi: 10.1007/s11709-023-0965-y

Abstract: An algorithm based on deep semantic segmentation called LC-DeepLab is proposed for detecting the trendsThe proposed method addresses the low accuracy of tunnel crack segmentation and the slow detection speedfusion module that extracts crack features across pixels is designed to improve the edges of crack segmentationFour classic semantic segmentation algorithms (fully convolutional network, pyramid scene parsing networkThe LC-DeepLab can achieve a real-time segmentation of 416 × 416 × 3 defect images with 46.98 f/s and

Keywords： tunnel engineering     crack segmentation     fast detection     DeepLabv3+     feature fusion     attention mechanism    

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Semantic composition of distributed representations for query subtopic mining None

Wei SONG, Ying LIU, Li-zhen LIU, Han-shi WANG

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 11,   Pages 1409-1419 doi: 10.1631/FITEE.1601476

Abstract: In this paper, we exploit and compare the main semantic composition of distributed representations forWe thoroughly investigate the impacts of semantic composition strategies and the types of data for learningThe empirical results show that distributed semantic representations can achieve outstanding performancefor query subtopic mining, compared with traditional semantic representations.

Keywords： Subtopic mining     Query intent     Distributed representation     Semantic composition    

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Digital twin-enabled smart facility management: A bibliometric review

Frontiers of Engineering Management doi: 10.1007/s42524-023-0254-4

Abstract: In recent years, the architecture, engineering, construction, and facility management (FM) industries have been applying various emerging digital technologies to facilitate the design, construction, and management of infrastructure facilities. Digital twin (DT) has emerged as a solution for enabling real-time data acquisition, transfer, analysis, and utilization for improved decision-making toward smart FM. Substantial research on DT for FM has been undertaken in the past decade. This paper presents a bibliometric analysis of the literature on DT for FM. A total of 248 research articles are obtained from the Scopus and Web of Science databases. VOSviewer is then utilized to conduct bibliometric analysis and visualize keyword co-occurrence, citation, and co-authorship networks; furthermore, the research topics, authors, sources, and countries contributing to the use of DT for FM are identified. The findings show that the current research of DT in FM focuses on building information modeling-based FM, artificial intelligence (AI)-based predictive maintenance, real-time cyber–physical system data integration, and facility lifecycle asset management. Several areas, such as AI-based real-time asset prognostics and health management, virtual-based intelligent infrastructure monitoring, deep learning-aided continuous improvement of the FM systems, semantically rich data interoperability throughout the facility lifecycle, and autonomous control feedback, need to be further studied. This review contributes to the body of knowledge on digital transformation and smart FM by identifying the landscape, state-of-the-art research trends, and future needs with regard to DT in FM.

Keywords： digital twin     building information modeling     facility management     semantic interoperability     artificial    

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Toward Wisdom-Evolutionary and Primitive-Concise 6G: A New Paradigm of Semantic Communication Networks Article

Ping Zhang, Wenjun Xu, Hui Gao, Kai Niu, Xiaodong Xu, Xiaoqi Qin, Caixia Yuan, Zhijin Qin, Haitao Zhao, Jibo Wei, Fangwei Zhang

Engineering 2022, Volume 8, Issue 1,   Pages 60-73 doi: 10.1016/j.eng.2021.11.003

Abstract: In particular, we aim to concretize the evolution path toward the WePCN by first conceiving a new semanticrepresentation framework, namely semantic base, and then establishing an intelligent and efficient semanticIn the IE-SC architecture, a semantic intelligence plane is employed to interconnect the semantic-empoweredphysical-bearing layer, network protocol layer, and application-intent layer via semantic informationWe also present a brief review of recent advances in semantic communications and highlight potential

Keywords： 6G     Semantic information     Semantic communication     Intelligent communication    

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Multi-color space threshold segmentation and self-learning k-NN algorithm for surge test EUT status

Jian HUANG,Gui-xiong LIU

Frontiers of Mechanical Engineering 2016, Volume 11, Issue 3,   Pages 311-315 doi: 10.1007/s11465-016-0376-z

Abstract: A multi-color space threshold segmentation and self-learning k-nearest neighbor algorithm

Keywords： multi-color space     k-nearest neighbor algorithm (k-NN)     self-learning     surge test    

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Detecting large-scale underwater cracks based on remote operated vehicle and graph convolutional neural network

Wenxuan CAO; Junjie LI

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 11,   Pages 1378-1396 doi: 10.1007/s11709-022-0855-8

Abstract: this paper, a large-scale underwater crack examination method is proposed based on image stitching and segmentationthan Fully convolutional networks (FCN), proving that GCN has great potential of application in image segmentation

Keywords： underwater cracks     remote operated vehicle     image stitching     image segmentation     graph convolutional    

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Vascular segmentation of neuroimages based on a prior shape and local statistics Research Articles

Yun TIAN, Zi-feng LIU, Shi-feng ZHAO

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 8,   Pages 1099-1108 doi: 10.1631/FITEE.1800129

Abstract: However, most of the vessel segmentation techniques ignore the existence of the isolated and redundantpoints in the segmentation results.In this study, we propose a vascular segmentation method based on a prior shape and local statistics.

Keywords： Vesselness filter     Neighborhood     Blood-vessel segmentation     Outlier    

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Incorporating target language semantic roles into a string-to-tree translation model Article

Chao SU, Yu-hang GUO, He-yan HUANG, Shu-min SHI, Chong FENG

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 10,   Pages 1534-1542 doi: 10.1631/FITEE.1601349

Abstract: However, it does not use any semantic information and tends to produce translations containing semanticIn this paper, we propose two methods to use semantic roles to improve the performance of the string-to-treetranslation model: (1) adding role labels in the syntax tree; (2) constructing a semantic role tree,Our methods enable the system to train and choose better translation rules using semantic information

Keywords： Machine translation     Semantic role     Syntax tree     String-to-tree    

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Interactive image segmentation with a regression based ensemble learning paradigm Article

Jin ZHANG, Zhao-hui TANG, Wei-hua GUI, Qing CHEN, Jin-ping LIU

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 7,   Pages 1002-1020 doi: 10.1631/FITEE.1601401

Abstract: To achieve fine segmentation of complex natural images, people often resort to an interactive segmentationHowever, when the foreground and background share some similar areas in color, the fine segmentationThis paper presents a novel interactive image segmentation method via a regression-based ensemble modeland semi-supervised learning is proposed to assist the training of MARS and TPSR by using the region segmentationFinally, the GraphCut is introduced and combined with the SVR ensemble results to achieve image segmentation

Keywords： Interactive image segmentation     Multivariate adaptive regression splines (MARS)     Ensemble learning     Thin-plate    

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SPSSNet: a real-time network for image semantic segmentation

Saqib Mamoon, Muhammad Arslan Manzoor, Fa-en Zhang, Zakir Ali, Jian-feng Lu,saqibmamoon@njust.edu.cn,arsalaan@njust.edu.cn,zhangfaen@ainnovation.com,alizakir@njust.edu.cn,lujf@njust.edu.cn

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 12,   Pages 1671-1814 doi: 10.1631/FITEE.1900697

Abstract: Although deep neural networks (DNNs) have achieved great success in semantic segmentation tasks, it isIn this paper, we propose a light-weight semantic segmentation network (SPSSN), which can efficiently
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Interactive medical image segmentation with self-adaptive confidence calibration

沈楚云,李文浩,徐琪森,胡斌,金博,蔡海滨,朱凤平,李郁欣,王祥丰

Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 9,   Pages 1332-1348 doi: 10.1631/FITEE.2200299

Abstract: Interactive medical image segmentation based on human-in-the-loop machine learning is a novel paradigmthat draws on human expert knowledge to assist medical image segmentation.To better use the interaction information at various timescales, we propose an interactive segmentationframework, called interactive MEdical image segmentation with self-adaptive Confidence CAlibration (Numerical experiments on different segmentation tasks show that MECCA can significantly improve short

Keywords： Medical image segmentation     Interactive segmentation     Multi-agent reinforcement learning     Confidence learning    

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Cost-effective resource segmentation in hierarchical mobile edge clouds Special Feature on Future Network-Research Article

Ming-shuang JIN, Shuai GAO, Hong-bin LUO, Hong-ke ZHANG

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 9,   Pages 1209-1220 doi: 10.1631/FITEE.1800203

Abstract: The fifth-generation (5G) network cloudification enables third parties to deploy their applications (e.g., edge caching and edge computing) at the network edge. Many previous works have focused on specific service strategies (e.g., cache placement strategy and vCPU provision strategy) for edge applications from the perspective of a certain third party by maximizing its benefit. However, there is no literature that focuses on how to efficiently allocate resources from the perspective of a mobile network operator, taking the different deployment requirements of all third parties into consideration. In this paper, we address the problem by formulating an optimization problem, which minimizes the total deployment cost of all third parties. To capture the deployment requirements of the third parties, the applications that they want to deploy are classified into two types, namely, computation-intensive ones and storage-intensive ones, whose requirements are considered as input parameters or constraints in the optimization. Due to the NP-hardness and non-convexity of the formulated problem, we have designed an elitist genetic algorithm that converges to the global optimum to solve it. Extensive simulations have been conducted to illustrate the feasibility and effectiveness of the proposed algorithm.

Keywords： Edge clouds     Edge computing     Edge caching     Resource segmentation     Virtual machine (VM) allocation    

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Segmentation and focus-point location based on boundary analysis in forest canopy hemispherical photography Article

Jia-yin SONG,Wen-long SONG,Jian-ping HUANG,Liang-kuan ZHU

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 8,   Pages 741-749 doi: 10.1631/FITEE.1601169

Abstract: In this study, our main focus was on using circular image region segmentation, which is the basis ofOn this basis, we proposed a segmentation method for the circular region in a forest canopy hemisphere

Keywords： Fisheye lens     Least squares method     Image segmentation     Ecology in image processing     Hemispherical photography    

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Beyond bag of latent topics: spatial pyramid matching for scene category recognition

Fu-xiang LU,Jun HUANG

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 10,   Pages 817-828 doi: 10.1631/FITEE.1500070

Abstract: topics by means of spatial pyramid, while the latent topics are obtained by using probabilistic latent semantic

Keywords： Scene category recognition     Probabilistic latent semantic analysis     Bag-of-words     Adaptive boosting    

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Title Author Date Type Operation

Optimal CNN-based semantic segmentation model of cutting slope images

Mansheng LIN; Shuai TENG; Gongfa CHEN; Jianbing LV; Zhongyu HAO

Journal Article

Fast detection algorithm for cracks on tunnel linings based on deep semantic segmentation

Journal Article

Semantic composition of distributed representations for query subtopic mining

Wei SONG, Ying LIU, Li-zhen LIU, Han-shi WANG

Journal Article

Digital twin-enabled smart facility management: A bibliometric review

Journal Article

Toward Wisdom-Evolutionary and Primitive-Concise 6G: A New Paradigm of Semantic Communication Networks

Ping Zhang, Wenjun Xu, Hui Gao, Kai Niu, Xiaodong Xu, Xiaoqi Qin, Caixia Yuan, Zhijin Qin, Haitao Zhao, Jibo Wei, Fangwei Zhang

Journal Article

Multi-color space threshold segmentation and self-learning k-NN algorithm for surge test EUT status

Jian HUANG,Gui-xiong LIU

Journal Article

Detecting large-scale underwater cracks based on remote operated vehicle and graph convolutional neural network

Wenxuan CAO; Junjie LI

Journal Article

Vascular segmentation of neuroimages based on a prior shape and local statistics

Yun TIAN, Zi-feng LIU, Shi-feng ZHAO

Journal Article

Incorporating target language semantic roles into a string-to-tree translation model

Chao SU, Yu-hang GUO, He-yan HUANG, Shu-min SHI, Chong FENG

Journal Article

Interactive image segmentation with a regression based ensemble learning paradigm

Jin ZHANG, Zhao-hui TANG, Wei-hua GUI, Qing CHEN, Jin-ping LIU

Journal Article

SPSSNet: a real-time network for image semantic segmentation

Saqib Mamoon, Muhammad Arslan Manzoor, Fa-en Zhang, Zakir Ali, Jian-feng Lu,saqibmamoon@njust.edu.cn,arsalaan@njust.edu.cn,zhangfaen@ainnovation.com,alizakir@njust.edu.cn,lujf@njust.edu.cn

Journal Article

Interactive medical image segmentation with self-adaptive confidence calibration

沈楚云,李文浩,徐琪森,胡斌,金博,蔡海滨,朱凤平,李郁欣,王祥丰

Journal Article

Cost-effective resource segmentation in hierarchical mobile edge clouds

Ming-shuang JIN, Shuai GAO, Hong-bin LUO, Hong-ke ZHANG

Journal Article

Segmentation and focus-point location based on boundary analysis in forest canopy hemispherical photography

Jia-yin SONG,Wen-long SONG,Jian-ping HUANG,Liang-kuan ZHU

Journal Article

Beyond bag of latent topics: spatial pyramid matching for scene category recognition

Fu-xiang LU,Jun HUANG

Journal Article