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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 convolutionalanalyze and identify the key components of cutting slope images in complex scenes and achieve rapid image-basedThis 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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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: In this paper, a large-scale underwater crack examination method is proposed based on image stitchingand segmentation.The graph convolutional neural network (GCN) was used to segment the stitched image.higher than Fully convolutional networks (FCN), proving that GCN has great potential of application in imagesegmentation and underwater image processing.

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

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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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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 segmentationThis paper presents a novel interactive image segmentation method via a regression-based ensemble modelFinally, the GraphCut is introduced and combined with the SVR ensemble results to achieve image segmentationvalidated that the proposed method is comparable with the state-of-the-art methods for in-teractive natural imagesegmentation.

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

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Deep learning in digital pathology image analysis: a survey

Shujian Deng, Xin Zhang, Wen Yan, Eric I-Chao Chang, Yubo Fan, Maode Lai, Yan Xu

Frontiers of Medicine 2020, Volume 14, Issue 4,   Pages 470-487 doi: 10.1007/s11684-020-0782-9

Abstract: In this paper, we comprehensively summarize recent DL-based image analysis studies in histopathology,including different tasks (e.g., classification, semantic segmentation, detection, and instance segmentation

Keywords： pathology     deep learning     segmentation     detection     classification    

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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 ofThe image boundary characteristics were defined and obtained based on the following: (1) an edge modelOn this basis, we proposed a segmentation method for the circular region in a forest canopy hemisphereimage, fitting the circular boundary and computing the center and radius by the least squares methodThe method was unrelated to the parameters of the image acquisition device.

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

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Survey on Extraction Methods of Transition Region

Liu Suolan,Yang Jingyu

Strategic Study of CAE 2007, Volume 9, Issue 9,   Pages 89-96

Abstract:

Image segmentation is treated as a key issue in image processing and Having the aid of extraction of transition region to segment image is a kind of burgeoning technology

Keywords： transition region     extraction     image segmentation     gradient method     non-gradient method    

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Pixel-level crack segmentation of tunnel lining segments based on an encoder–decoder network

Frontiers of Structural and Civil Engineering 2024, Volume 18, Issue 5,   Pages 681-698 doi: 10.1007/s11709-024-1048-4

Abstract: This study proposes a novel encoder–decoder structure, CrackRecNet, for semantic segmentation of liningAn image acquisition equipment is designed based on a camera, 3-dimensional printing (3DP) bracket andA tunnel concrete structure crack (TCSC) image data set, containing images collected from a double-shieldsuch as brightness adjustment, pixel resolution adjustment, flipping, splitting and annotation, 2880 image

Keywords： tunnel lining segment     crack detection     semantic segmentation     convolutional neural network     encoder–decoder    

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Investigation of crack segmentation and fast evaluation of crack propagation, based on deep learning

Frontiers of Structural and Civil Engineering 2024, Volume 18, Issue 4,   Pages 516-535 doi: 10.1007/s11709-024-1040-z

Abstract: findings indicate that the U-Net is more robust and efficient than the SegNet for identifying crack segmentation

Keywords： deep learning     crack segmentation     crack propagation     encoder−decoder     recurrent neural network    

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Spacecraft damage infrared detection algorithm for hypervelocity impact based on double-layer multi-target segmentation Research Article

Xiao YANG, Chun YIN, Sara DADRAS, Guangyu LEI, Xutong TAN, Gen QIU,yinchun.86416@163.com,chunyin@uestc.edu.cn

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 4,   Pages 571-586 doi: 10.1631/FITEE.2000695

Abstract: temperature change characteristics in the sampled data of the infrared video stream and reconstruct the imageto obtain the infrared reconstructed image (IRRI) reflecting the defect characteristics.The designed segmentation objective function is used to ensure the effectiveness of results for noisemulti-objective evolutionary algorithm based on decomposition (MOEA/D) is used for optimization to ensure damage segmentation

Keywords： Hypervelocity impact damage     Defect detection     Gaussian mixture model     Image segmentation    

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Turbidity-adaptive underwater image enhancement method using image fusion

Frontiers of Mechanical Engineering 2022, Volume 17, Issue 3, doi: 10.1007/s11465-021-0669-8

Abstract: In this paper, we propose a turbidity-adaptive underwater image enhancement method.Based on the detection result, different image enhancement strategies are designed to deal with the problemThe proposed method is verified by an underwater image dataset captured in real underwater environmentThe result is evaluated by image metrics including structure similarity index measure, underwater colorimage quality evaluation metric, and speeded-up robust features.

Keywords： turbidity     underwater image enhancement     image fusion     underwater robots     visibility    

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Kernel sparse representation for MRI image analysis in automatic brain tumor segmentation None

Ji-jun TONG, Peng ZHANG, Yu-xiang WENG, Dan-hua ZHU

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 4,   Pages 471-480 doi: 10.1631/FITEE.1620342

Abstract: The segmentation of brain tumor plays an important role in diagnosis, treatment planning, and surgicalThe precise segmentation of brain tumor can help clinicians obtain its location, size, and shape informationWe propose a fully automatic brain tumor segmentation method based on kernel sparse coding.To assess the segmentation performance, the segmentation results are uploaded to the online evaluationIt is competitive to the other groups in the brain tumor segmentation challenge.

Keywords： Brain tumor segmentation     Kernel method     Sparse coding     Dictionary learning    

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Gradient-based compressive image fusion

Yang CHEN,Zheng QIN

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 3,   Pages 227-237 doi: 10.1631/FITEE.1400217

Abstract: We present a novel image fusion scheme based on gradient and scrambled block Hadamard ensemble (SBHE)In the fusion phase, the image gradient is calculated to reflect the abundance of its contour informationBy compositing the gradient of each image, gradient-based weights are obtained, with which compressiveFinally, inverse transformation is applied to the coefficients derived from fusion, and the fused imageIn addition, different image fusion application scenarios are applied to explore the scenario adaptability

Keywords： Compressive sensing (CS)     Image fusion     Gradient-based image fusion     CS-based image fusion    

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Edge detection of steel plates at high temperature using image measurement

Qiong Zhou, Qi An

Frontiers of Mechanical Engineering 2009, Volume 4, Issue 1,   Pages 77-82 doi: 10.1007/s11465-009-0013-1

Abstract: An edge detection method for the measurement of steel plate’s thermal expansion is proposed in this paper, where the shrinkage of a steel plate is measured when temperature drops. First, images are picked up by an imaging system; a method of regional edge detection based on grayscales’ sudden change is then applied to detect the edges of the steel plate; finally, pixel coordinates of the edge position are transformed to physical coordinates through calibration parameters. The experiment shows that the real-time, high precision, and non-contact measurement of the steel plate’s edge position under high temperature can be realized using the imaging measurement method established in this paper.

Keywords： thermal expansion     image measurement     edge detection     image calibration    

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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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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

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

Wenxuan CAO; Junjie LI

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

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

Deep learning in digital pathology image analysis: a survey

Shujian Deng, Xin Zhang, Wen Yan, Eric I-Chao Chang, Yubo Fan, Maode Lai, Yan Xu

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

Survey on Extraction Methods of Transition Region

Liu Suolan,Yang Jingyu

Journal Article

Pixel-level crack segmentation of tunnel lining segments based on an encoder–decoder network

Journal Article

Investigation of crack segmentation and fast evaluation of crack propagation, based on deep learning

Journal Article

Spacecraft damage infrared detection algorithm for hypervelocity impact based on double-layer multi-target segmentation

Xiao YANG, Chun YIN, Sara DADRAS, Guangyu LEI, Xutong TAN, Gen QIU,yinchun.86416@163.com,chunyin@uestc.edu.cn

Journal Article

Turbidity-adaptive underwater image enhancement method using image fusion

Journal Article

Kernel sparse representation for MRI image analysis in automatic brain tumor segmentation

Ji-jun TONG, Peng ZHANG, Yu-xiang WENG, Dan-hua ZHU

Journal Article

Gradient-based compressive image fusion

Yang CHEN,Zheng QIN

Journal Article

Edge detection of steel plates at high temperature using image measurement

Qiong Zhou, Qi An

Journal Article

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

Journal Article