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Digital image correlation-based structural state detection through deep learning

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 1,   Pages 45-56 doi: 10.1007/s11709-021-0777-x

Abstract: This paper presents a new approach for automatical classification of structural state through deep learningCNN can extract the structural state information from the vibration signals and classify them; 2) the detection

Keywords： structural state detection     deep learning     digital image correlation     vibration signal     steel frame    

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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 speed

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

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A deep feed-forward neural network for damage detection in functionally graded carbon nanotube-reinforced

Frontiers of Structural and Civil Engineering 2021, Volume 15, Issue 6,   Pages 1453-1479 doi: 10.1007/s11709-021-0767-z

Abstract: This paper proposes a new Deep Feed-forward Neural Network (DFNN) approach for damage detection in functionallyObtained results indicate that the proposed DFNN model is able to give sufficiently accurate damage detection

Keywords： damage detection     deep feed-forward neural networks     functionally graded carbon nanotube-reinforced composite    

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Machine vision-based automatic fruit quality detection and grading

Frontiers of Agricultural Science and Engineering doi: 10.15302/J-FASE-2023532

Abstract:

● A machine vision-based prototype system was developed for fruit grading.

Keywords： Computer and machine vision     convolution neural network     deep learning     defective fruit detection     fruit    

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Development Strategy of Quantum-Based Deep Geophysical Exploration Technology and Equipment

Lin Jun, Ji Yanju, Zhao Jing , Tong Xunqian , Yi Xiaofeng

Strategic Study of CAE 2022, Volume 24, Issue 4,   Pages 156-166 doi: 10.15302/J-SSCAE-2022.04.017

Abstract: system, magnetic vector gradient detection system, superconducting gravity detection system, and cold-atomabsolute-gravity exploration system during deep resource exploration.mineral resource exploration and revealing of Earth’s deep structure.In this study, we propose new ideas for the development of quantum geophysical deep detection technologyIt has conducted a range of applications in deep mineral exploration, including the successful detection

Keywords： mineral resources     deep detection     quantum-based high-precision measurement     superconducting quantum-basedelectromagnetic detection     superconducting gravity detection     cold-atom absolute-gravity detection    

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Real-Time Detection of Cracks on Concrete Bridge Decks Using Deep Learning in the Frequency Domain Article

Qianyun Zhang,Kaveh Barri,Saeed K. Babanajad,Amir H. Alavi

Engineering 2021, Volume 7, Issue 12,   Pages 1786-1796 doi: 10.1016/j.eng.2020.07.026

Abstract:

This paper presents a vision-based crack detection approach for concrete bridge decks using an integratedThe proposed 1D-CNN-LSTM method exhibits superior performance in comparison with existing deep learningThe fast implementation of the 1D-CNN-LSTM algorithm makes it a promising tool for real-time crack detection

Keywords： Crack detection     Concrete bridge deck     Deep learning     Real-time    

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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: deep learning (DL) has achieved state-of-the-art performance in many digital pathology analysis tasksstudies in histopathology, including different tasks (e.g., classification, semantic segmentation, detection

Keywords： pathology     deep learning     segmentation     detection     classification    

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A deep Q-learning network based active object detection model with a novel training algorithm for service Research Article

Shaopeng LIU, Guohui TIAN, Yongcheng CUI, Xuyang SHAO

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 11,   Pages 1673-1683 doi: 10.1631/FITEE.2200109

Abstract:

This paper focuses on the problem of (AOD). AOD is important for to complete tasks in the family environment, and leads robots to approach the target object by taking appropriate moving actions. Most of the current AOD methods are based on reinforcement learning with low training efficiency and testing accuracy. Therefore, an AOD model based on a (DQN) with a novel training algorithm is proposed in this paper. The DQN model is designed to fit the Q-values of various actions, and includes state space, feature extraction, and a multilayer perceptron. In contrast to existing research, a novel training algorithm based on memory is designed for the proposed DQN model to improve training efficiency and testing accuracy. In addition, a method of generating the end state is presented to judge when to stop the AOD task during the training process. Sufficient comparison experiments and ablation studies are performed based on an AOD dataset, proving that the presented method has better performance than the comparable methods and that the proposed training algorithm is more effective than the raw training algorithm.

Keywords： Active object detection     Deep Q-learning network     Training method     Service robots    

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Detection of damage locations and damage steps in pile foundations using acoustic emissions with deep

Alipujiang JIERULA, Tae-Min OH, Shuhong WANG, Joon-Hyun LEE, Hyunwoo KIM, Jong-Won LEE

Frontiers of Structural and Civil Engineering 2021, Volume 15, Issue 2,   Pages 318-332 doi: 10.1007/s11709-021-0715-y

Abstract: The aim of this study is to propose a new detection method for determining the damage locations in pilefoundations based on deep learning using acoustic emission data.First, the damage location is simulated using a back propagation neural network deep learning model withFinally, a new damage detection and evaluation method for pile foundations is proposed.

Keywords： pile foundations     damage location     acoustic emission     deep learning     damage step    

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Deep Learning in Medical Ultrasound Analysis: A Review Review

Shengfeng Liu, Yi Wang, Xin Yang, Baiying Lei, Li Liu, Shawn Xiang Li, Dong Ni, Tianfu Wang

Engineering 2019, Volume 5, Issue 2,   Pages 261-275 doi: 10.1016/j.eng.2018.11.020

Abstract: Deep learning has recently emerged as the leading machine learning tool in various research fields, andDeep learning also shows huge potential for various automatic US image analysis tasks.This review first briefly introduces several popular deep learning architectures, and then summarizesdiscusses their applications in various specific tasks in US image analysis, such as classification, detectionFinally, the open challenges and potential trends of the future application of deep learning in medical

Keywords： Deep learning     Medical ultrasound analysis     Classification     Segmentation     Detection    

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Usability perceptions and beliefs about smart thermostats by chi-square test, signal detection theory, and fuzzy detection theory in regions of Mexico

Pedro PONCE, Therese PEFFER, Arturo MOLINA

Frontiers in Energy 2019, Volume 13, Issue 3,   Pages 522-538 doi: 10.1007/s11708-018-0562-2

Abstract: This paper proposes the use of a signal detection theory (SDT), fuzzy detection theory (FDT), and chi-square

Keywords： thermostats     perceptions     beliefs     signal detection theory (SDT)     fuzzy signal detection theory (FSDT)     chi-square    

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Advances in airborne microorganisms detection using biosensors: A critical review

Frontiers of Environmental Science & Engineering 2021, Volume 15, Issue 3, doi: 10.1007/s11783-021-1420-8

Abstract: In recent years, the detection technology for airborne microorganisms has developed rapidly; it can be

Keywords： Biosensor     Airborne microorganisms     Microbiological detection technology    

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Recent advances in SERS detection of perchlorate

Jumin Hao, Xiaoguang Meng

Frontiers of Chemical Science and Engineering 2017, Volume 11, Issue 3,   Pages 448-464 doi: 10.1007/s11705-017-1611-9

Abstract: Development of novel detection methods for perchlorate with the potential for field use has been an urgentperchlorate in water and other media with an emphasis on the development of SERS substrates for perchlorate detection

Keywords： perchlorate     SERS     detection     substrate     modification     nanostructure    

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A fast antibiotic detection method for simplified pretreatment through spectra-based machine learning

Frontiers of Environmental Science & Engineering 2022, Volume 16, Issue 3, doi: 10.1007/s11783-021-1472-9

Abstract:

• A spectral machine learning approach is proposed for predicting mixed antibiotic.

Keywords： Antibiotic contamination     Spectral detection     Machine learning    

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Development of Pulsed Radiation Detection Technology

Ouyang Xiaoping

Strategic Study of CAE 2008, Volume 10, Issue 4,   Pages 44-55

Abstract: Pulse radiation detection has found its various applications in scientific researches, including nuclearThese diagnostic techniques and their relative detection systems, the design principle, the parameters

Keywords： fission reaction     fusion reaction     pulse radiation detection     detecting system     neutron detection     gamma-raydetection    

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Title Author Date Type Operation

Digital image correlation-based structural state detection through deep learning

Journal Article

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

Journal Article

A deep feed-forward neural network for damage detection in functionally graded carbon nanotube-reinforced

Journal Article

Machine vision-based automatic fruit quality detection and grading

Journal Article

Development Strategy of Quantum-Based Deep Geophysical Exploration Technology and Equipment

Lin Jun, Ji Yanju, Zhao Jing , Tong Xunqian , Yi Xiaofeng

Journal Article

Real-Time Detection of Cracks on Concrete Bridge Decks Using Deep Learning in the Frequency Domain

Qianyun Zhang,Kaveh Barri,Saeed K. Babanajad,Amir H. Alavi

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

A deep Q-learning network based active object detection model with a novel training algorithm for service

Shaopeng LIU, Guohui TIAN, Yongcheng CUI, Xuyang SHAO

Journal Article

Detection of damage locations and damage steps in pile foundations using acoustic emissions with deep

Alipujiang JIERULA, Tae-Min OH, Shuhong WANG, Joon-Hyun LEE, Hyunwoo KIM, Jong-Won LEE

Journal Article

Deep Learning in Medical Ultrasound Analysis: A Review

Shengfeng Liu, Yi Wang, Xin Yang, Baiying Lei, Li Liu, Shawn Xiang Li, Dong Ni, Tianfu Wang

Journal Article

Usability perceptions and beliefs about smart thermostats by chi-square test, signal detection theory, and fuzzy detection theory in regions of Mexico

Pedro PONCE, Therese PEFFER, Arturo MOLINA

Journal Article

Advances in airborne microorganisms detection using biosensors: A critical review

Journal Article

Recent advances in SERS detection of perchlorate

Jumin Hao, Xiaoguang Meng

Journal Article

A fast antibiotic detection method for simplified pretreatment through spectra-based machine learning

Journal Article

Development of Pulsed Radiation Detection Technology

Ouyang Xiaoping

Journal Article