Article
Computer Science, Artificial Intelligence
Ricard Lado-Roige, Marco A. Perez
Summary: The goal of video motion magnification techniques is to amplify small movements in videos that were previously invisible. This has applications in various fields such as biomedicine, deepfake detection, structural modal analysis, and predictive maintenance. However, distinguishing small motions from noise is challenging, especially when magnifying subtle, sub-pixel movements. This work introduces a state-of-the-art model based on the Swin Transformer that offers improved tolerance to noisy inputs and produces higher-quality outputs with less noise, blurriness, and artifacts compared to prior techniques. The improved output image quality enables more precise measurements for applications relying on magnified video sequences and may facilitate further advancements in video motion magnification techniques in new technical fields.
KNOWLEDGE-BASED SYSTEMS
(2023)
Article
Physics, Multidisciplinary
Jintao Wang, Longshen Liu, Mingzhou Lu, Cedric Okinda, Daniela Lovarelli, Marcella Guarino, Mingxia Shen
Summary: This study proposes a method using deep learning and machine vision to estimate the respiratory rate of broilers by analyzing the belly fluctuation signal in video data. The experiments show that this method has high accuracy and can monitor the health status of broilers contactlessly and stress-freely.
FRONTIERS IN PHYSICS
(2022)
Article
Robotics
Haram Kim, Sangil Lee, Junha Kim, H. Jin Kim
Summary: Event cameras perform better than frame cameras in challenging scenarios, but cannot completely replace frame cameras in normal situations. To leverage the advantages of both cameras, we propose a heterogeneous stereo camera system that combines an event and a frame camera to estimate real-time semi-dense disparity by matching heterogeneous data.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2023)
Article
Chemistry, Multidisciplinary
Teja Potocnik, Peter J. Christopher, Ralf Mouthaan, Tom Albrow-Owen, Oliver J. Burton, Chennupati Jagadish, Hark Hoe Tan, Timothy D. Wilkinson, Stephan Hofmann, Hannah J. Joyce, Jack A. Alexander-Webber
Summary: We present a high-throughput method for identifying and characterizing individual nanowires, and for designing electrode patterns with high alignment accuracy. Our method utilizes an optimized marker system called LithoTag, which allows for nanometer-scale position determination of nanostructures. By incorporating computer vision algorithms, we can obtain location and property data for individual nanowires. Experimental results demonstrate the effectiveness of this method in automating nanodevice processing and improving fabrication efficiency.
Article
Chemistry, Multidisciplinary
Jesus Salido, Vanesa Lomas, Jesus Ruiz-Santaquiteria, Oscar Deniz
Summary: This study focuses on automatic detection of handguns in video surveillance images using three convolutional neural network models. Results show that including pose information can reduce false positives, with the YOLOv3 model trained on dataset including pose information demonstrating the best performance.
APPLIED SCIENCES-BASEL
(2021)
Article
Engineering, Civil
Jothi S. Thiyagarajan, Dionysius M. Siringoringo, Samten Wangchuk, Yozo Fujino
Summary: In the past earthquakes, damages on lights and utility poles mounted on elevated highway or railway bridges were observed, caused by excessive response amplification during large earthquakes. Investigation of seismic performance is needed to avoid this amplification, and non-contact vision sensing is seen as a promising alternative to conventional contact sensors for vibration testing. The non-contact vision method is effectively capable of obtaining the natural frequency and damping ratio of structures under ambient conditions.
SMART STRUCTURES AND SYSTEMS
(2021)
Article
Robotics
Wenkang Fan, Zhuohui Zheng, Wankang Zeng, Yinran Chen, Hui-Qing Zeng, Hong Shi, Xiongbiao Luo
Summary: Accurate localization of vessels and neurovascular bundles is crucial in surgery, but surgeons may have difficulty in perceiving and protecting these structures. A new surgical video pulsatile motion magnification method is proposed to assist surgeons in recognizing these structures more easily, with experimental results showing its superiority over current motion magnification approaches.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2021)
Article
Robotics
Ahalya Ravendran, Mitch Bryson, Donald G. Dansereau
Summary: This research develops an image processing technique using burst photography to improve the robustness and accuracy of 3D reconstruction in low light conditions. The method shows improved performance in challenging light-constrained scenes and has potential applications for robots operating in environments with limited light.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Review
Energy & Fuels
Tahir Hussain, Muhammad Hussain, Hussain Al-Aqrabi, Tariq Alsboui, Richard Hill
Summary: The past two decades have witnessed an increase in the deployment of photovoltaic installations worldwide as an effort to mitigate the consequences of global warming. The manufacturing of solar cells involves a rigorous process starting from silicon extraction. The growing demand poses various challenges for manual quality inspection, leading researchers to explore convolutional neural network architectures for automated inspection.
Article
Chemistry, Physical
Chao-Min Huang, Anjelica Kucinic, Joshua A. Johnson, Hai-Jun Su, Carlos E. Castro
Summary: Recent studies have shown that integrating molecular dynamics-based computer-aided engineering with computer-aided design allows for the rapid construction of large three-dimensional DNA assemblies with control over their geometry, mechanics, and dynamics, expanding the scope of structural complexity and design capabilities for DNA assemblies.
Article
Chemistry, Physical
Hao Zhou, Fuhai Liu, Jinkai Chen, Junchao Wang, Yun Wu, Jin Chen, Shiyuan Chang, Lianbin Xia, Chi Zhang, Jingyang Jiang, Kang Dong, Chenhao Zhang, Lingling Sun, Weipeng Xuan, Pengfei Zhao, Hao Jin, Shurong Dong, Jikui Luo
Summary: Developing efficient triboelectric nanogenerators (TENGs) is crucial for their applications. However, the current design processes cannot effectively optimize complex TENG structures. Therefore, a universal computer aided design automation method is proposed to generate optimal power output TENG designs with designated matching resistance. Through simulations and verification, a designed FR-TENG with optimized output power and impedance is used in a self-powered wireless environmental monitoring system.
Article
Robotics
John Z. Zhang, Shuo Yang, Gengshan Yang, Arun L. Bishop, Swaminathan Gurumurthy, Deva Ramanan, Zachary Manchester
Summary: SLoMo is a novel framework for transferring skilled motions from real-life videos to legged robots. It works through three stages and does not require expert animators or expensive equipment. The approach converts videos into motion primitives that can be executed reliably by robots.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2023)
Article
Chemistry, Multidisciplinary
Alberto Trentino, Jacob Madsen, Andreas Mittelberger, Clemens Mangler, Toma Susi, Kimmo Mustonen, Jani Kotakoski
Summary: By utilizing a near ultrahigh vacuum system and advanced imaging techniques, researchers have overcome various difficulties in the structural engineering of 2D materials, successfully preparing and fully characterizing atomically clean free-standing graphene with controlled defect distribution.
Article
Food Science & Technology
Maimunah Mohd Ali, Norhashila Hashim, Siti Khairunniza Bejo, Mahirah Jahari, Nurul Aqilah Shahabudin
Summary: This review presents the external and internal quality attributes of pineapples and discusses the application of chemometrics and data mining in evaluating their quality. Non-destructive technologies, such as spectroscopy-based, computer vision, imaging-based, acoustic, ultrasound, and instrument-based sensing technologies, are promising alternatives to conventional methods for monitoring the quality of pineapples.
TRENDS IN FOOD SCIENCE & TECHNOLOGY
(2023)
Article
Robotics
Katsuma Inoue, Yasuo Kuniyoshi, Katsushi Kagaya, Kohei Nakajima
Summary: Soft continuum bodies utilize the deformability of materials to generate flexible functionalities, but modeling the morphology dynamics is challenging. This study introduces a novel framework for automatic extraction of skeletal dynamics from video of soft continuum bodies, applied in animal motion analysis and soft robotics design.
Article
Construction & Building Technology
Biqin Dong, Zhentao Gu, Qiwen Qiu, Yuqing Liu, Weijian Ding, Feng Xing, Shuxian Hong
CONSTRUCTION AND BUILDING MATERIALS
(2018)
Article
Agriculture, Multidisciplinary
Qiwen Qiu, Renyuan Qin, Josh H. M. Lam, Alvin M. C. Tang, Mike W. K. Leung, Denvid Lau
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2019)
Review
Green & Sustainable Science & Technology
Jiayu Chen, Qiwen Qiu, Yilong Han, Denvid Lau
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2019)
Article
Engineering, Manufacturing
Ao Zhou, Qiwen Qiu, Cheuk Lun Chow, Denvid Lau
COMPOSITES PART A-APPLIED SCIENCE AND MANUFACTURING
(2020)
Review
Construction & Building Technology
Qiwen Qiu
STRUCTURAL CONTROL & HEALTH MONITORING
(2020)
Article
Engineering, Mechanical
Qiwen Qiu, Denvid Lau
Summary: The study explores the impact of vehicle noise on the acoustic-laser technique in defect detection of FRP-bonded structures, finding that vehicle noise raises the noise floor in the measured frequency spectrum and induces noise-related peaks. Vehicle noise has a greater effect on detecting large defects and a denoising scheme is proposed to address this issue.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2021)
Article
Computer Science, Interdisciplinary Applications
Qiwen Qiu, Jian-Guo Dai
Summary: This study presents a methodology for numerical simulation of chloride diffusivity in mortar subjected to corrosion-induced cracking using X-ray microcomputed tomography. The effects of multiple material phases on chloride diffusion are studied, and accurate local material information allows evaluation of diffusivity and spatial distribution characteristics of mortar under different corrosion times.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
(2021)
Article
Construction & Building Technology
Qiwen Qiu, Denvid Lau
Summary: This paper proposes the integration of You Only Look Once (YOLO) into an unmanned aerial vehicle (UAV) for real-time crack detection in tiled sidewalks. Different network architectures of YOLOv2-tiny, Darknet19-based YOLOv2, ResNet50-based YOLOv2, YOLOv3, and YOLOv4-tiny are compared to improve accuracy and speed of detection. The results show that ResNet50-based YOLOv2 and YOLOv4-tiny offer excellent accuracy and speed, and remarkable ability in detecting small cracks. They also demonstrate good adaptability to environmental conditions such as shadows, rain, and motion-induced blurriness. The evaluation suggests the appropriate altitude and scanning area for the YOLO-UAV-based platform to achieve remote, reliable, and rapid crack detection.
AUTOMATION IN CONSTRUCTION
(2023)
Article
Materials Science, Characterization & Testing
Qiwen Qiu
Summary: The paper presents a progressive methodology that combines X-ray micro computed tomography (μCT) and finite element analysis (FEA) to test the thermal conductivity of wood at the mesoscale level. The analytical wood conductivities from μCT-based FEA agree well with those from the theoretical analysis and the existing experimental findings. Using μCT-based FEA also enables the numerical evaluation of the effects of grain orientation, porosity, and water saturation degree on thermal conductivity of wood.
NDT & E INTERNATIONAL
(2023)
Article
Materials Science, Multidisciplinary
Qiwen Qiu
Summary: The present study establishes a new methodology, micro computed tomography based finite element analysis (mu CT-based FEA), for evaluating the influence of internal defects on the thermal conductivity of fiber-reinforced polymer (FRP). The investigation reveals that unfilled bug holes and delamination decrease the effective thermal conductivity of FRP and cause sub-surface heat concentration, while needle-like cavities have negligible effect on thermal conductivity. Increasing the water saturation degree of defects leads to an exponential increase in thermal conductivity, especially for large air cavities or delamination.
MATERIALS TODAY COMMUNICATIONS
(2023)
Article
Construction & Building Technology
Qiwen Qiu, Jihua Zhu, Jian-Guo Dai
CONSTRUCTION AND BUILDING MATERIALS
(2020)
Proceedings Paper
Materials Science, Characterization & Testing
Renyuan Qin, Qiwen Qiu, Denvid Lau
NONDESTRUCTIVE CHARACTERIZATION AND MONITORING OF ADVANCED MATERIALS, AEROSPACE, CIVIL INFRASTRUCTURE, AND TRANSPORTATION VIX
(2020)
Proceedings Paper
Materials Science, Multidisciplinary
Qiwen Qiu, Denvid Lau
NONDESTRUCTIVE CHARACTERIZATION AND MONITORING OF ADVANCED MATERIALS, AEROSPACE, CIVIL INFRASTRUCTURE, AND TRANSPORTATION XIII
(2019)
Proceedings Paper
Materials Science, Multidisciplinary
Qiwen Qiu, Denvid Lau
NONDESTRUCTIVE CHARACTERIZATION AND MONITORING OF ADVANCED MATERIALS, AEROSPACE, CIVIL INFRASTRUCTURE, AND TRANSPORTATION XII
(2018)
Article
Construction & Building Technology
Jia Liang, Qipeng Zhang, Xingyu Gu
Summary: A lightweight PCSNet-based segmentation model is developed to address the issues of insufficient performance in feature extraction and boundary loss information. The introduction of generalized Dice loss improves prediction performance, and the visualization of class activation mapping enhances model interpretability.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Gilsu Jeong, Minhyuk Jung, Seongeun Park, Moonseo Park, Changbum Ryan Ahn
Summary: This study introduces a contextual audio-visual approach to recognize multi-equipment activities in tunnel construction sites, improving monitoring effectiveness. Tested against real-world operation data, the model achieved remarkable results, emphasizing the potential of contextual multimodal models in enhancing operational efficiency in complex construction sites.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Jin Wang, Zhigao Zeng, Pradip Kumar Sharma, Osama Alfarraj, Amr Tolba, Jianming Zhang, Lei Wang
Summary: This study presents a dual-path network for pavement crack segmentation, combining Convolutional Neural Network (CNN) and transformer. A lightweight CNN encoder is used for local feature extraction, while a novel transformer encoder integrates high-low frequency attention mechanism and efficient feedforward network for global feature extraction. Additionally, a complementary fusion module is introduced to aggregate intermediate features extracted from both encoders. Evaluation on three datasets confirms the superior performance of the proposed network.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Pierre Gilibert, Romain Mesnil, Olivier Baverel
Summary: This paper introduces a flexible method for crafting 2D assemblies adaptable to various geometric assumptions in the realm of sustainable construction. By utilizing digital fabrication technologies and optimization approaches, precise control over demountable buildings can be achieved, improving mechanical performance and sustainability.
AUTOMATION IN CONSTRUCTION
(2024)
Review
Construction & Building Technology
Jorge Loy-Benitez, Myung Kyu Song, Yo-Hyun Choi, Je-Kyum Lee, Sean Seungwon Lee
Summary: This paper discusses the advancement of tunnel boring machines (TBM) through the application of artificial intelligence. It highlights the significance of AI-based management subsystems for automatic TBM operations and presents recent contributions in this field. The paper evaluates modeling, monitoring, and control subsystems and suggests research paths for integrating existing management subsystems into TBM automation.
AUTOMATION IN CONSTRUCTION
(2024)
Review
Construction & Building Technology
Alireza Shamshiri, Kyeong Rok Ryu, June Young Park
Summary: This paper reviews the application of text mining and natural language processing in the construction field, highlighting the need for automation and minimizing manual tasks. The study identifies potential research opportunities in strengthening overlooked construction aspects, coupling diverse data formats, and leveraging pre-trained language models and reinforcement learning.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Zhengyi Chen, Hao Wang, Keyu Chen, Changhao Song, Xiao Zhang, Boyu Wang, Jack C. P. Cheng
Summary: This study proposes an improved coverage path planning system that leverages building information modeling and robotic configurations to optimize coverage performance in indoor environments. Experimental validation shows the effectiveness and applicability of the system. Future research will focus on further enhancing coverage ratio and optimizing computation time.
AUTOMATION IN CONSTRUCTION
(2024)
Review
Construction & Building Technology
Yonglin Fu, Junjie Chen, Weisheng Lu
Summary: This study presents a review of human-robot collaboration (HRC) in modular construction manufacturing (MCM), focusing on tasks, human roles, and interaction levels. The review found that HRC solutions are applicable to various MCM tasks, with a primary focus on timber component production. It also revealed the diverse collaborative roles humans can play and the varying levels of interaction with robots.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Qiong Liu, Shengbo Cheng, Chang Sun, Kailun Chen, Wengui Li, Vivian W. Y. Tam
Summary: This paper presents an approach to enhance the path-following capability of concrete printing by integrating steel cables into the printed mortar strips, and validates the feasibility and effectiveness of this approach through experiments.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Honghu Chu, Lu Deng, Huaqing Yuan, Lizhi Long, Jingjing Guo
Summary: The study proposes a method called Cascade CATransUNet for high-resolution crack image segmentation. This method combines the coordinate attention mechanism and self-cascaded design to accurately segment cracks. Through a customized feature extraction architecture and an optimized boundary loss function, the proposed method achieves impressive segmentation performance on HR images and demonstrates its practicality in UAV crack detection tasks.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Daniel Lamas, Andres Justo, Mario Soilan, Belen Riveiro
Summary: This paper introduces a new method for creating synthetic point clouds of truss bridges and demonstrates the effectiveness of a deep learning approach for semantic and instance segmentation of these point clouds. The proposed methodology has significant implications for the development of automated inspection and monitoring systems for truss bridges.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Kahyun Jeon, Ghang Lee, Seongmin Yang, Yonghan Kim, Seungah Suh
Summary: This study proposes two enhanced unsupervised text classification methods for domain-specific non-English text. The results of the tests show that these methods achieve excellent performance on Korean building defect complaints, outperforming state-of-the-art zero-shot and few-shot text classification methods, with minimal data preparation effort and computing resources.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Yoonhwa Jung, Julia Hockenmaier, Mani Golparvar-Fard
Summary: This study introduces a transformer-based natural language processing model, UNIfORMATBRIDGE, that automatically labels activities in a project schedule with Uniformat classification. Experimental results show that the model performs well in matching unstructured schedule data to Uniformat classifications. Additionally, the study highlights the importance of this method in developing new techniques.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
De-Graft Joe Opoku, Srinath Perera, Robert Osei-Kyei, Maria Rashidi, Keivan Bamdad, Tosin Famakinwa
Summary: This paper introduces a digital twin technology combining Building Information Modelling and the Internet of Things for the construction industry, aiming to optimize building conditions. The technology is implemented in a university library, successfully achieving real-time data capture and visual representation of internal conditions.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Zaolin Pan, Yantao Yu
Summary: The construction industry faces safety and workforce shortages globally, and worker-robot collaboration is seen as a solution. However, robots face challenges in recognizing worker intentions in construction. This study tackles these challenges by proposing a fusion method and investigating the best granularity for recognizing worker intentions. The results show that the proposed method can recognize multi-granular worker intentions effectively, contributing to seamless worker-robot collaboration in construction.
AUTOMATION IN CONSTRUCTION
(2024)
