Intelligent Crack Detection and Quantification in the Concrete Bridge: A Deep Learning-Assisted Image Processing Approach by Licun Yu, Shuanhai He, Xiaosong Liu, Shuqing Jiang, Shuiying Xiang

“…Compared with the conventional image processing-based crack detection method, the deep learning-assisted image processing approach leads to higher detection accuracy and lower computation cost. …”
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Information Design for “Weak Signal” detection and processing in Economic Intelligence: A case study on Health resources by Sahbi Sidhom, Philippe Lambert

“…In our approach to implement the ID, the processes cover the development of a knowledge management (KM) process in the context of EI. …”
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7. Detecting Bias in Plastic Surgery Residency Application Letters of Recommendation using Natural Language Processing by Tanay Nagar, Sarah Jung, Peter Wirth, Alyssa Schappe, Amorn N. Salyapongse

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A Defect Detection Method for Flexible Thermal Control Film Manufacturing Process Driven by Digital Twin by LI Rongyi, TIAN Shuaiqi, DAI Mingqiu, XU Youqiang, LI Xianbin, HOU Kailin

“…By decoupling system functional modules and adopting distributed service governance, high concurrency and high availability online monitoring of the film manufacturing process is achieved. Then, a vacuum coating defect detection algorithm is designed, integrating adaptive convolution + spatial pyramid module, enhancing multi-scale features through FPN/ PAN, optimizing anchor boxes and lightweight design, achieving a detection speed of 140 FPS at 91. 5% accuracy. …”
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Ultrasonic Nondestructive Testing of Li-ion Batteries for Anomaly Detection and Quality Control: Applications and Signal Processing by Mohammadreza Kari

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Fleet‐Wide Data‐Driven Model Generation Process for Residual‐Based Fault Detection in Wind Energy by Théodore Raymond, Sylvie Charbonnier, Christophe Bérenguer, Alexis Lebranchu

“…These condition‐based maintenance processes generally rely on data‐driven residual indicators, measuring the difference between a measured value and an estimation made by a normal behavior model. …”
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Efficient processing of side-scan sonar images and fast detection of sparse targets in large-scale images by Xi Zhao, Qiangqiang Yuan, Jiadan Xu

“…Therefore, this paper proposes an efficient method for real-time side-scan sonar (SSS) image processing and detection of sparse targets in large-scale images. …”
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Improving the efficiency and security of passport control processes at airports by using the R-CNN object detection model by Elhoucine Ouassam, Yassine Dabachine, Nabil Hmina, Belaid Bouikhalene

“… The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. …”
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The data dimensionality reduction and bad data detection in the process of smart grid reconstruction through machine learning. by Bo Yu, Zheng Wang, Shangke Liu, Xiaomin Liu, Ruixin Gou

“…To detect false data injection attacks (FDIAs) in power grid reconstruction and solve the problem of high data dimension and bad abnormal data processing in the power system, thereby achieving safe and stable operation of the power grid system, this study introduces machine learning methods to explore the detection of FDIAs. …”
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Fault Detection Method Using Auto-Associative Shared Nearest Neighbor Kernel Regression for Industrial Processes by Minseok Kim, Eunkyeong Kim, Seunghwan Jung, Baekcheon Kim, Jinyong Kim, Sungshin Kim

“…To address these challenges, we propose an auto-associative shared nearest neighbor kernel regression method for fault detection in complex industrial processes. Inspired by attention mechanisms, the proposed approach assigns higher weights to relevant training data. …”
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Multimedia Detection and Processing of Remote-Sensing Image of Small Target Combined with Variable Neighborhood Search Algorithm by Yaqin Wang, Maolong Qiu

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Solution‐Processable Van Der Waals Heterojunctions on Silicon for Self‐Powered Photodetectors with High Responsivity and Detectivity by Yuansheng Ge, Da Lei, Chaojun Zhang, Quan Zhang, Jinlong Mu, Jing Li

“…Abstract The high density of surface states on silicon has long impeded the development of high‐performance photodetectors, leading to excessive dark leakage currents that adversely affect responsivity and detectivity. Herein, an all‐solution‐processable method is presented for fabricating photodetectors through consecutive spray‐coating of a conductive metal‐organic framework (MOF, Cu3(HHTP)2) and metallic Ti3C2 MXene to form van der Waals dual junctions on a silicon substrate. …”
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Real‐time object detection for unmanned vehicles in Bangladesh: Dataset, implementation and evaluation by Muhammad Liakat Ali, Topu Biswas, Shahin Akter, Mohammed Farhan Jawad, Hadaate Ullah

“…Abstract Automated vehicle detection within the advanced application framework of autonomous vehicles significantly enhances road safety compared to human drivers on roads and highways. …”
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Toward Optimal Placement of Spatial Sensors to Detect Poisson-Distributed Targets by Mingyu Kim, Harun Yetkin, Daniel J. Stilwell, Jorge Jimenez, Saurav Shrestha, Nina Stark

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From LLMs to Randomness: Analyzing Program Input Efficacy With Resource and Language Metrics by Gavin Black, Eric Yocam, Varghese Mathew Vaidyan, Gurcan Comert, Yong Wang

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Detecting Source Code Plagiarism in Student Assignment Submissions Using Clustering Techniques by Raddam Sami Mehsen, Majharoddin M. Kazi, Hiren Joshi

“…To implement our approach, we utilize the Python programming language along with relevant libraries, providing a robust and efficient system for source code plagiarism detection in student assignment submissions. …”
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Detection of Defects on Metal Surfaces Based on Deep Learning by Onur Cem Han, Uğurhan Kutbay

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Narrowband Theta Investigations for Detecting Cognitive Mental Load by Silviu Ionita, Daniela Andreea Coman

“…The way in which EEG signals reflect mental tasks that vary in duration and intensity is a key topic in the investigation of neural processes concerning neuroscience in general and BCI technologies in particular. …”
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Prediabetes detection in unconstrained conditions using wearable sensors by Dimitra Tatli, Vasileios Papapanagiotou, Aris Liakos, Apostolos Tsapas, Anastasios Delopoulos

“…This research explores the feasibility of using wearable continuous glucose monitoring along with smartwatches with embedded inertial sensors to collect glucose measurements and acceleration signals respectively, for the early detection of prediabetes. We propose a methodology based on signal processing and machine learning techniques. …”
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Learning spatial‐frequency interaction for generalizable deepfake detection by Tianbo Zhai, Kaiyin Lu, Jiajun Li, Yukai Wang, Wenjie Zhang, Peipeng Yu, Zhihua Xia

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