Online Meta-Recommendation of CUSUM Hyperparameters for Enhanced Drift Detection by Jessica Fernandes Lopes, Sylvio Barbon Junior, Leonimer Flávio de Melo

“…The Cumulative Sum (CUSUM) method, based on calculating the cumulative values within a time series, is commonly used for change detection due to its early detection of small drifts, simplicity, low computational cost, and robustness to noise. …”
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Infrared Detection of Substation Objects Using the Visible Light Spectrum by Andreas Anael Pereira Gomes, Leandra Ulbricht, Francisco Ganacim, Leonardo Göbel Fernandes, Anselmo Pombeiro, Nara Bobko, Eduardo Félix Ribeiro Romaneli

“…Our proposed method allows using an object detector with results comparable to other works that performed detection directly on the infrared domain while requiring no significant changes to the model architecture. …”
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AN ITERATIVE PROCEDURE FOR OUTLIER DETECTION IN GSTAR(1;1) MODEL by Nur'ainul Miftahul Huda, Utriweni Mukhaiyar, Nurfitri Imro'ah

“…The process is repeated by detecting outliers and adding them to the model until a GSTAR model is obtained with no outliers detected. …”
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Java deserialization vulnerability defense technologybased on run-time detection by LI Yulin, CHEN Libo, LIU Yujiang, DU Wenlong, XUE Zhi

“…Following an examination of numerous publicly known Java deserialization vulnerabilities, a runtime detection-based defense technology solution for Java deserialization vulnerabilities was proposed. …”
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Ripe Tomato Detection Algorithm Based on Improved YOLOv9 by Yan Wang, Qianjie Rong, Chunhua Hu

“…To ensure the accuracy of inspection results, You Only Look Once version 9 (YOLOv9) has been explored as a fruit detection algorithm. To tackle the challenge of identifying tomatoes and the low accuracy of small object detection in complex environments, we propose a ripe tomato recognition algorithm based on an enhanced YOLOv9-C model. …”
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Dog facial landmarks detection and its applications for facial analysis by George Martvel, Anna Zamansky, Giulia Pedretti, Chiara Canori, Ilan Shimshoni, Annika Bremhorst

“…We additionally provide a benchmark for dog facial landmarks detection and demonstrate two case studies for landmark detection models trained on the DogFLW. …”
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Non-Destructive Detection of Fruit Quality: Technologies, Applications and Prospects by Jingyi Liu, Jun Sun, Yasong Wang, Xin Liu, Yingjie Zhang, Haijun Fu

“…Fruit quality testing plays a crucial role in the advancement of fruit industry, which is related to market competitiveness, consumer satisfaction and production process optimization. In recent years, nondestructive testing technology has become a research hotspot due to its outstanding advantages. …”
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Nighttime Vehicle Detection Algorithm Based on Improved YOLOv7 by Fan Zhang

“…Second, a lightweight efficient feature fusion network (GS-EFF) is constructed to optimize multi-scale feature alignment by combining the jump connection and GSConv modules to reduce the information loss in the feature fusion process and lower the number of parameters. The Soft-EloU-NMS post-processing algorithm is further proposed to effectively reduce the leakage detection rate of dense small targets by fusing the multi-dimensional evaluation of overlap, center distance and aspect ratio. …”
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Electrochemical Detection of Sequence-Specific DNA with the Amplification of Gold Nanoparticles by Yuzhong Zhang, Zhen Wang, Yuehong Wang, Lei Huang, Wei Jiang, Mingzhu Wang

“…Scanning electron microscopy (SEM) and electrochemical impedance spectra (EIS) were used to investigate the film assembly process. The DNA hybridization events were monitored by differential pulse voltammetry (DPV), and adriamycin was used as the electrochemical indicator. …”
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Road Damage Detection Using Yolov9-Based Imagery by Febrian Akbar Azhari, Tatang Rohana, Kiki Ahmad Baihaqi, Ahmad Fauzi

“…An annotated dataset of road images was used during the model training and testing process. The results show that the YOLOv9 model can accurately detect road damage. …”
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Verification of the Reliability of an Automated Urine Test Strip Colorimetric Program Using Colorimetric Analysis: Survey Study by Keigo Inagaki, Daisuke Tsuriya, Takuya Hashimoto, Katsumasa Nakamura

“…The image taken with a smartphone camera on top of the photography box was judged by this program. This program used Accelerated KAZE to perform image-matching processing to reduce the effect of misalignment during photography. …”
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Calibration and uncertainty quantification for deep learning-based drought detection by Mengxue Zhang, Miguel-Ángel Fernández-Torres, Kai-Hendrik Cohrs, Gustau Camps-Valls

“…Deep learning models have recently succeeded in detecting extreme climate events and promise to uncover and understand droughts further. …”
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Prospects for detecting the couplings of axion-like particle with neutrinos at the CEPC by Chong-Xing Yue, Xin-Yang Li, Xiao-Chen Sun

“…Abstract We explore the possibility of detecting the couplings of axion-like particle (ALP) with leptons from their loop-level impact on the ALP couplings to electroweak (EW) gauge bosons via the signal process at the circular electron positron collider (CEPC) and obtain prospective sensitivities to the ALP-lepton couplings. …”
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Detecting phishing gangs via taint analysis on the Ethereum blockchain by Kangrui Huang, Weili Chen, Zibin Zheng

“…Experimental results indicate that the proposed framework can be used to build a uniform platform to monitor every account on the Ethereum blockchain for early warning of phishing scams and detection of the phishers' money laundering and cashing process.…”
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Optimized Detection Algorithm for Vertical Irregularities in Vertical Curve Segments by Rong Xie, Chunjun Chen

“…The inertial reference method was then applied to process the acceleration and relative displacement data between the detection beam and the track, yielding virtual irregularities. …”
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Study on PV Defect Detection Based on CWE YOLOv8 by Xiaojuan Zhang, Ruixu Yao, Bo Jing, Xiaoxuan Jiao, Mengdi Ren

“…A lightweight EfficientHead detection head is also introduced to boost the model’s accuracy and robustness in complex detection scenarios. …”
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Hard-coded backdoor detection method based on semantic conflict by Anxiang HU, Da XIAO, Shichen GUO, Shengli LIU

“…The current router security issues focus on the mining and utilization of memory-type vulnerabilities, but there is low interest in detecting backdoors.Hard-coded backdoor is one of the most common backdoors, which is simple and convenient to set up and can be implemented with only a small amount of code.However, it is difficult to be discovered and often causes serious safety hazard and economic loss.The triggering process of hard-coded backdoor is inseparable from string comparison functions.Therefore, the detection of hard-coded backdoors relies on string comparison functions, which are mainly divided into static analysis method and symbolic execution method.The former has a high degree of automation, but has a high false positive rate and poor detection results.The latter has a high accuracy rate, but cannot automate large-scale detection of firmware, and faces the problem of path explosion or even unable to constrain solution.Aiming at the above problems, a hard-coded backdoor detection algorithm based on string text semantic conflict (Stect) was proposed since static analysis and the think of stain analysis.Stect started from the commonly used string comparison functions, combined with the characteristics of MIPS and ARM architectures, and extracted a set of paths with the same start and end nodes using function call relationships, control flow graphs, and branching selection dependent strings.If the strings in the successfully verified set of paths have semantic conflict, it means that there is a hard-coded backdoor in the router firmware.In order to evaluate the detection effect of Stect, 1 074 collected device images were tested and compared with other backdoor detection methods.Experimental results show that Stect has a better detection effect compared with existing backdoor detection methods including Costin and Stringer: 8 hard-coded backdoor images detected from image data set, and the recall rate reached 88.89%.…”
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Knowledge Error Detection via Textual and Structural Joint Learning by Xiaoyu Wang, Xiang Ao, Fuwei Zhang, Zhao Zhang, Qing He

“…Current methods for knowledge graph error detection primarily focus on graph structure and overlook the importance of textual information in error detection. …”
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A Method for Detecting Tomato Maturity Based on Deep Learning by Song Wang, Jianxia Xiang, Daqing Chen, Cong Zhang

“…The modeling of global and local information is realized through the self-attention mechanism, which improves the generalization ability and feature extraction ability of the model, thereby bringing higher detection accuracy. Secondly, the C2f convolution in the neck section is replaced with Distribution Shifting Convolution, so that the model can better process spatial information and further improve the object detection accuracy. …”
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Myocarditis Detection Using Proximal Policy Optimization and Mutual Learning by Asadi Srinivasulu, Sivaram Rajeyyagari

“…To address class imbalance, a proximal policy optimization (PPO)-based algorithm is utilized, significantly improving the training process by preventing abrupt policy shifts and stabilizing them. …”
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