Early detection of risky spatio-temporal congestion in urban traffic by Shaobo Sui, Dan Xu, Mingyang Bai, Xiaoke Zhang, Zhaojun Mao, Daqing Li

“…In this article, we develop a detection method for risky congestion based on its spatio-temporal evolution feature, which can detect risky spatio-temporal congestion clusters (SCCs) when they are small. …”
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Mixed Gas Detection and Temperature Compensation Based on Photoacoustic Spectroscopy by Sun Chao, Hu Runze, Liu Niansong, Ding Jianjun

“…Experimental results show that, compared to the traditional SVM algorithm, the KNN-SVM algorithm performs better in gas classification prediction, with an accuracy rate of 99.167% and an AUC indicator of 99.375%, enhancing the accuracy of gas detection. In response to the impact of temperature on the system during the experimental process, a WOA-BP temperature compensation model was established to compensate for temperature in gas concentration detection. …”
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Capacity Constraint Analysis Using Object Detection for Smart Manufacturing by Hafiz Mughees Ahmad, Afshin Rahimi, Khizer Hayat

“…The increasing adoption of Deep Learning (DL)-based Object Detection (OD) models in smart manufacturing has opened up new avenues for optimizing production processes. …”
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Automated detection of hospital outbreaks: A systematic review of methods. by Brice Leclère, David L Buckeridge, Pierre-Yves Boëlle, Pascal Astagneau, Didier Lepelletier

“…<h4>Results</h4>Twenty-nine studies were included. The detection algorithms were grouped into 5 categories: simple thresholds (n = 6), statistical process control (n = 12), scan statistics (n = 6), traditional statistical models (n = 6), and data mining methods (n = 4). …”
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Deepfake detection method based on patch-wise lighting inconsistency by Wenxuan WU, Wenbo ZHOU, Weiming ZHANG, Nenghai YU

“…The rapid development and widespread dissemination of deepfake techniques has caused increased concern.The malicious application of deepfake techniques also poses a potential threat to the society.Therefore, how to detect deepfake content has become a popular research topic.Most of the previous deepfake detection algorithms focused on capturing subtle forgery traces at pixel level and have achieved some results.However, most of the deepfake algorithms ignore the lighting information before and after generation, resulting in some lighting inconsistency between the original face and the forged face, which provided the possibility of using lighting inconsistency to detect deepfake.A corresponding algorithm was designed from two perspectives: introducing lighting inconsistency information and designing a network structure module for a specific task.For the introduction of lighting task, a new network structure was derived by designing the corresponding channel fusion method to provide more lighting inconsistency information to the network feature extraction layer.In order to ensure the portability of the network structure, the process of feature channel fusion was placed before the network extraction information, so that the proposed method can be fully planted to common deepfake detection networks.For the design of the network structure, a deepfake detection method was proposed for lighting inconsistency based on patch-similarity from two perspectives: network structure and loss function design.For the network structure, based on the characteristic of inconsistency between the forged image tampering region and the background region, the extracted features were chunked in the network feature layer and the feature layer similarity matrix was obtained by comparing the patch-wise cosine similarity to make the network focus more on the lighting inconsistency.On this basis, based on the feature layer similarity matching scheme, an independent ground truth and loss function was designed for this task in a targeted manner by comparing the input image with the untampered image of this image for patch-wise authenticity.It is demonstrated experimentally that the accuracy of the proposed method is significantly improved for deepfake detection compared with the baseline method.…”
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Weed detection on embedded systems using computer vision algorithms by D. Shadrin, S. Illarionova, R. Kasatov, M. Akimenkova, G. Rudensky, E. Erhan

“…They allow one to automate data analysis process and to make decisions faster. However, the weed detection task in agriculture requires not only high recognition accuracy, but also fast computations on portable devices with low memory availability that makes it possible to embed computer vision systems on unmanned aerial vehicles (UAVs). …”
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Automatic Acne Detection Model Based on Improved YOLOv7 by Delong Zhang, Chunyang Jin, Zhidong Zhang, Xiyuan Cao, Chenyang Xue

“…The mAP is 4.57% higher than the initial model and better than the general object detection model. This model holds promise for effectively managing patient health status and providing valuable assistance to physicians in the diagnostic process.…”
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Detection-Oriented Evaluation of SAR Dexterous Barrage Jamming Effectiveness by Hai Zhu, Sinong Quan, Shiqi Xing, Haoyu Zhang, Yun Ren

“…Starting from the detection, it divides the evaluation process into two stages: (1) for the case in which the target can be detected under the jamming scenario, two feature parameters, namely, the target exposion area and target relative magnitude, are extracted; (2) for the case in which the target cannot be detected under the jamming scenario, another three feature parameters, namely, jamming relative magnitude, average edge brightness, and local information entropy, are extracted. …”
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Terahertz Metasurfaces for Polarization Manipulation and Detection: Principles and Emerging Applications by Yongliang Liu, Yifei Xu, Bo Yu, Wenwei Liu, Zhengren Zhang, Hua Cheng, Shuqi Chen

“…Abstract Terahertz frequencies locating between microwave and infrared regions can record and process optical information for next‐generation information technology such as 6G communication. …”
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Radar Detection Simulation by Digital Twins of Target and Antenna System by A. S. Grigoriev, A. A. Kazantsev, A. M. Terentyev, B. S. Stavtsev

“…Development of an algorithmic support for simulating the radar detection process using digital twins of the antenna system and the observation object.Materials and methods. …”
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Underground helmet detection algorithm based on improved YOLOv8s by Jiaru YANG, Yinan QIN, Tianxu LI, Han ZHUANG

“…In the process of coal mine underground operation, the safety helmet is the most direct and effective protective measure, and it is an important measure to ensure the safety of miners. …”
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Target Detection and Characterization of Multi-Platform Remote Sensing Data by Koushikey Chhapariya, Emmett Ientilucci, Krishna Mohan Buddhiraju, Anil Kumar

“…Conventionally, target detection in remote sensing has relied on statistical methods that typically assume a linear process for image formation. …”
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QEDetr: DETR with Query Enhancement for Fine-Grained Object Detection by Chenguang Dong, Shan Jiang, Haijiang Sun, Jiang Li, Zhenglei Yu, Jiasong Wang, Jiacheng Wang

“…Fine-grained object detection aims to accurately localize the object bounding box while identifying the specific model of the object, which is more challenging than conventional remote sensing object detection. …”
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An Interpretable Siamese Attention Res-CNN for Fingerprint Spoofing Detection by Chengsheng Yuan, Zhenyu Xu, Xinting Li, Zhili Zhou, Junhao Huang, Ping Guo

“…Consequently, a fingerprint presentation attack detection (PAD) strategy is proposed to ensure the security of these systems. …”
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Transfer Learning-Based Anomaly Detection System for Autonomous Vehicle by Md. Humayun Kabir, Mohammad Nadib Hasan, Ahmad, Hassan Jaki

“…A system that combines the control of a physical process with computing technology and communication networks is called a cyber–physical system (CPS). …”
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Real Time Person Detection and Distance Estimation Using Stereovision by Rachidi Oumayma, Bououlid Idrissi Badr, Ed-Dahmani Chafik

“…Pedestrian detection constitutes a fundamental component of Advanced Driver Assistance Systems (ADAS). playing a pivotal role in ensuring road safety and reducing the risk of accidents. …”
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Detection of Movement and Lead-Popping Artifacts in Polysomnography EEG Data by Nishanth Anandanadarajah, Amlan Talukder, Deryck Yeung, Yuanyuan Li, David M. Umbach, Zheng Fan, Leping Li

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Reusable Biosensor for Easy RNA Detection from Unfiltered Saliva by Paweł Wityk, Agata Terebieniec, Robert Nowak, Jacek Łubiński, Martyna Mroczyńska-Szeląg, Tomasz Wityk, Dorota Kostrzewa-Nowak

“…Biosensors are transforming point-of-care diagnostics by simplifying the detection process and enabling rapid, accurate testing. …”
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RADAR: Reasoning AI-Generated Image Detection for Semantic Fakes by Haochen Wang, Xuhui Liu, Ziqian Lu, Cilin Yan, Xiaolong Jiang, Runqi Wang, Efstratios Gavves

“…Specifically, RADAR contains a specialized multimodal LLM to process given images and detect semantic fakes. To improve the generalization ability, we further incorporate ChatGPT as an assistor to detect unrealistic components in grounded text descriptions. …”
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Optimizing credit card fraud detection with random forests and SMOTE by P. Sundaravadivel, R. Augustian Isaac, D. Elangovan, D. KrishnaRaj, V. V. Lokesh Rahul, R. Raja

“…Subsequently, various techniques are employed to pre-process the unprocessed data and visually present the outcomes through the use of exploratory data analysis (EDA). …”
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