A novel criterion for crack detection in beam structures by frequency response functions by Nguyen Tien Khiem, Tran Thanh Hai, Le Khanh Toan, Nguyen Thi Lan, Ho Quang Quyet

“… The frequency response function (FRF) is a fruitful attribute that includes almost all dynamical characteristics of a structure such as natural frequencies and modes, damping coefficients, or resonance and antiresonance conceptions. …”
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Security Paper Design with Frequency-Selective Structure for X-Band Electromagnetic Detection System by Sang-Hwa Lee, Min-Sik Kim, Jong-Kyu Kim, Jong-In Lim, Ic-Pyo Hong

“…This study designed and fabricated a frequency-selective structure-based security paper for the electromagnetic detection system of a security gate, which aims to prevent leakage of confidential documents. …”
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Seismic Damage Detection of Moment Resisting Frame Structures Using Time-Frequency Features by Dongwang Tao, Qiang Ma, Shanyou Li

“…To detect seismic damage of moment resisting frame (MRF) structures, a data-driven method using the fractal dimension (FD) of time-frequency feature (TFF) of structural seismic dynamic responses at measured stories is extended and refined. …”
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Damage Detection in Beam Structures Based on Frequency-Domain Analysis Methods for Nonlinear Systems by Wenbo Zhang, Xiaoyue Guo, Liangliang Cheng, Bo Zhang

“…Conventional detection methods based on the frequency response function (FRF) in linear systems tend to fail when small early damage occurs in engineered structures. …”
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Structural Damage Detection Based on Sparrow Search Algorithm by Ziyan Ma, Xi Peng, Fengjiang Qin, Qiuwei Yang, Bin Xu

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A damage zone detection method in concrete hydraulic structures based on multi-frequency ultrasonic characteristics by Jinchao Wang, Ming Chen, Nian Zhu, Houcheng Liu

“…Different damaged areas of concrete structures exhibit distinct characteristics of frequency acoustic signals, and these multi-frequency ultrasonic characteristics were studied in this research to improve the detection method of damaged areas in concrete hydraulic structures. …”
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Influence of Coupled Structural Parameters of Photoconductive Antennas on the Terahertz Narrowband Detection Performance of High Sensitivity and Frequency Selection by Zhonggang Xiong, Linyu Chen, Zhong Liu, Shuai Kang

“…The results prove that the THz frequency selection detection range of the coupled PCA can be designed to 0.1∼1.0 THz. …”
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Time–Frequency Characteristics of Vehicle–Bridge Interaction System for Structural Damage Detection Using Multi-Synchrosqueezing Transform by Mingzhe Gao, Xinqun Zhu, Jianchun Li

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Numerical study of the response of dynamic parameters to defects in composite structures by Grigorii S. Serovaev, Valery P. Matveenko

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Environmental Factors in Structural Health Monitoring—Analysis and Removal of Effects from Resonance Frequencies by Rims Janeliukstis, Lasma Ratnika, Liga Gaile, Sandris Rucevskis

“…The current study focuses on developing a damage detection methodology that is applicable to the long-term monitoring of such structures. …”
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Hyperspectral Anomaly Detection Using Dual-Branch Network Based on Frequency Domain Learning by Xiaoyi Wang, Jun Du, Qingxuan Lv, Peng Wang, Xianchao Zhang, Jian Cheng, Henry Leung

“…Existing deep learning-based hyperspectral anomaly detection methods often overlook frequency domain features, hindering the ability to effectively distinguish between background and anomalies. …”
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Screening and Artifact Detection of RFI in Sentinel-1A Time-Series Images Combining Change Detection Techniques With Structural Similarity Index by Zhizheng Zhang, Gaofeng Shu, Yabo Huang, Lin Wu, Ning Li

Subjects: “…Image change detection…”
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Crack Detection of Fan Blade Based on Natural Frequencies by Mengyao Yu, Sheng Fu, Yinbo Gao, Hao Zheng, Yonggang Xu

“…A simple method was developed to detect damage based on a discrete mathematical model for fan blades using changes in natural frequencies combined with a fluid-structure analysis. …”
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Direct brain recordings reveal implicit encoding of structure in random auditory streams by Julian Fuhrer, Kyrre Glette, Jugoslav Ivanovic, Pål Gunnar Larsson, Tristan Bekinschtein, Silvia Kochen, Robert T. Knight, Jim Tørresen, Anne-Kristin Solbakk, Tor Endestad, Alejandro Blenkmann

“…Our work provides a comprehensive picture of the neural correlates of automatic encoding of implicit structure that can be the crucial substrate for the swift detection of patterns and unexpected events in the environment.…”
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Frequency-Domain Collaborative Lightweight Super-Resolution for Fine Texture Enhancement in Rice Imagery by Zexiao Zhang, Jie Zhang, Jinyang Du, Xiangdong Chen, Wenjing Zhang, Changmeng Peng

“…However, existing images often suffer from texture blurring and contour shifting due to equipment and environment limitations, which affects the detection performance. In view of the fact that pests and diseases affect the whole situation and tiny details are mostly localized, we propose a rice image reconstruction method based on an adaptive two-branch heterogeneous structure. …”
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Data-driven multi-fault detection in pipelines utilizing frequency response function and artificial neural networks by Hussein A. M. Hussein, Sharafiz B. Abdul Rahim, Faizal B. Mustapha, Prajindra S. Krishnan, Nawal Aswan B. Abdul Jalil

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Radio frequency based detection of specific and nonspecific protein interaction by Annesha Mazumder, Arunangshu Biswas, Tapan K. Sau, Prabhakar Bhimalapuram, Azeemuddin Syed

“…A simulation-based analysis performed using High Frequency Structure Simulator (HFSS) corroborates the finding. …”
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Tampered text detection via RGB and frequency relationship modeling by Yuxin WANG, Boqiang ZHANG, Hongtao XIE, Yongdong ZHANG

“…In recent years, the widespread dissemination of tampered text images on the Internet constitutes an important threat to the security of text images.However, the corresponding tampered text detection (TTD) methods have not been sufficiently explored.The TTD task aims to locate all text regions in an image while judging whether the text regions have been tampered with according to the authenticity of the texture.Thus, different from the general text detection task, TTD task further needs to perceive the fine-grained information for real-world and tampered text classification.TTD task has two main challenges.One the one hand, due to the high similarity in texture between real-world texts and tampered texts, TTD methods that only learn from RGB domain features have limited capability to distinguish these two-category texts well.On the other hand, as the different detecting difficulty exists in real-world texts and tampered texts, the network cannot well balance the learning process of the two-category texts, resulting in the imbalance detection performance between real-world and tampered texts.Compared with RGB domain features, the discontinuity of text texture in frequency domain can help the network to identify the authenticity of text instances.Accordingly, a new TTD method based on RGB and frequency information relationship modeling was proposed.The features in the RGB and frequency domains were extracted by independent feature extractors respectively.Thus, the identification ability of tampered texture can be enhanced by introducing frequency information during the texture perception.Then, a global RGB-frequency relationship module (GRM) was introduced to model the texture authenticity relationship between different text instances.GRM referred to the RGB-frequency features of other text instances in the same image to assist in judging the authenticity of the current text instance, which solved the problem of imbalanced detection performance.Furthermore, a new TTD dataset (Tampered-SROIE) was proposed to evaluate the effectiveness of proposed method, which contains 986 images (626 training images and 360 test images).By evaluating on the Tampered-SROIE, the proposed method obtains 95.97% and 96.80% in F-measure for real-world and tampered texts respectively and reduces the imbalanced detection accuracy by 1.13%.The proposed method will give new insights to the TTD community from the perspective of network structure and detection strategy.Tampered-SROIE also provides an evaluation benchmark for future TTD methods.…”
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A Frequency Domain-Enhanced Transformer for Nighttime Object Detection by Yaru Li, Li Shen

“…Our approach integrates physics-prior enhancement to improve the visibility of objects in low-light conditions, frequency domain feature extraction to capture structural information potentially lost in the spatial domain, and window cross-attention fusion that efficiently combines complementary features while reducing computational complexity, significantly improving detection performance without increasing the parameter count. …”
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A Study on the Feasibility of Natural Frequency-Based Crack Detection by Xutao Sun, Sinniah Ilanko, Yusuke Mochida, Rachael C. Tighe

“…Owing to the long-standing statement that natural frequency-based crack detection is not sensitive enough to localised damage to identify small cracks, many natural frequency-based crack detection methods are validated by detecting cracks of moderate size. …”
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