Detecting Malicious Anomalies in Heavy-Duty Vehicular Networks Using Long Short-Term Memory Models by Mark J. Potvin, Sylvain P. Leblanc

“…We conducted a series of experiments to evaluate both detection systems by utilizing a simulated attack representation to generate anomalies. …”
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Use of Attack Graphs in Security Systems by Vivek Shandilya, Chris B. Simmons, Sajjan Shiva

“…This not only gives the simplified representation of the system, but also allows prioritizing the security properties whose violations are of greater concern, for both detection and repair. We present a survey and critical study of state-of-the-art technologies in attack graph generation and use in security system. …”
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Farsi License Plate Detection and Recognition Based on Characters Features by Sedigheh Ghofrani, Mehran Rasouli

“…The experimental results show that our proposed method achieves appropriate performance for both detection and recognition of the Iranian license plates.…”
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Interpretable Chinese Fake News Detection With Chain-of-Thought and In-Context Learning by Bingyi Liu, Anqi Wang, Chengqian Xia

“…Experiments show that our model improves both detection accuracy and interpretability, advancing the field of explainable AI in FND task.…”
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Robust Miner Detection in Challenging Underground Environments: An Improved YOLOv11 Approach by Yadong Li, Hui Yan, Dan Li, Hongdong Wang

“…Experimental results demonstrate that the proposed method outperforms various improved algorithms and state-of-the-art detection models in both detection performance and robustness, providing important technical support and reference for coal miner safety assurance and intelligent mine management.…”
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A Review of the Recent Trends in Mobile Malware Evolution, Detection, and Analysis by Seetah Almarri, Alanoud Bodokhi, Mounir Frikha

“…The rapid rise of smartphones and mobile applications has fostered an environment conducive to the advancement of mobile malware, presenting considerable obstacles for both detection and mitigation efforts. This analysis delves into the latest developments in mobile malware, underscoring the shift from basic threats to more complex forms of attacks, including ransomware, spyware, and banking trojans. …”
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Automatic nuclei segmentation in H&E stained breast cancer histopathology images. by Mitko Veta, Paul J van Diest, Robert Kornegoor, André Huisman, Max A Viergever, Josien P W Pluim

“…The evaluation was done in terms of both detection accuracy (sensitivity and positive predictive value) and segmentation accuracy (Dice coefficient). …”
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Edge-guided feature fusion network for RGB-T salient object detection by Yuanlin Chen, Zengbao Sun, Cheng Yan, Ming Zhao

“…Our approach achieves superior performance, demonstrating the effectiveness of the proposed modules in improving both detection accuracy and boundary refinement.DiscussionThe results highlight the importance of integrating cross-modal information and edge-guided fusion in RGB-T SOD. …”
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Automated Cattle Head and Ear Pose Estimation Using Deep Learning for Animal Welfare Research by Sueun Kim

“…Comprehensive datasets were constructed from images of Japanese Black cattle, collected under natural conditions and annotated for both detection and pose estimation tasks. The proposed framework achieved mean average precision (mAP) values of 0.79 for head detection and 0.71 for left ear detection and mean absolute error (MAE) of approximately 8–9° for pose estimation, demonstrating reliable performance across diverse orientations. …”
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Detection and localization of copy-move tampering along with adversarial attack in a digital image by Anjali Diwan, Anil K. Roy

“…This improvement in both detection accuracy and speed makes our approach a valuable contribution to the field of digital image forensics.…”
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A statistical sensing method by utilizing Wi-Fi CSI subcarriers: Empirical study and performance enhancement by Tao Deng, Bowen Zheng, Rui Du, Fan Liu, Tony Xiao Han

“…Within the OFDM communication framework, this work derives sensing outcomes for both detection and estimation by harnessing the CSI from every individual measured subcarrier, subsequently consolidating these outcomes. …”
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Design and analysis of secure communication protocol in the internet of things environment by Xiaoyan Huo

“…Research findings demonstrate that the newly proposed device-to-device secure communication protocol surpasses conventional secure communication protocols with regard to both detection rate and false detection rate. It not only offers robust resistance against hacker intrusions but also sustains a high level of recognition accuracy across diverse noisy environments. …”
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Battery System Fault Detection: A Data-Driven Aggregation and Augmentation Strategy by Zhiming Zhang, Dan Zhang, Dejun Li, Yi Liu, Jiong Yang

“…Comprehensive experimental evaluations demonstrate that our approach achieves marked improvements in both detection accuracy and robustness compared to conventional methods. …”
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Detection and Defense: Student-Teacher Network for Adversarial Robustness by Kyoungchan Park, Pilsung Kang

“…., CIFAR-10, CIFAR-100, and TinyImagenet, we demonstrate the superiority of our method in both detection and defense compared with state-of-the-art methods. …”
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Multi-Standard Speculative Decision Feedback Equalizer for PAMN Wireline Receiver by Mohamed Ahmed, Mohamed O. Abouzeid, Tawfiq Musah

“…Simulink simulations were used to discuss the parallel and multi-layer operation of the proposed receiver in both detection and equalization modes. The results from the model also show no performance degradation from the new receiver architecture when configured for PAM8/6/4/3/2 operation. …”
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Application of an Impedimetric Technique for the Detection of Lytic Infection of Salmonella spp. by Specific Phages by Lara R. P. Amorim, Joana G. L. Silva, Paul A. Gibbs, Paula C. Teixeira

“…From the sample analysis, based on conductance (G) measurements (37°C), the infection could be detected, by observation of both detection-time delay and distinct curve trends. …”
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Accident Detection and Flow Prediction for Connected and Automated Transport Systems by Yi Zhang, Fang Liu, Sheng Yue, Yuxuan Li, Qianwei Dong

“…Allowing for the dynamic spread of traffic flow over time, from upstream to downstream and from accident lanes to other lanes, a spatiotemporal Markov model is established to predict the evolution of traffic flow after accident by introducing the grid as state detection unit and fitting the spatiotemporal evolution with the parameter space mean speed to match the need of both detection accuracy and monitoring scope. Compared with actual accident data, the validation results indicate that the proposed methods present a good performance in accident detection with the accident detection rate as 87.72% and a higher precision rate than both SVM (support vector machine) and ANN (artificial neural network) models in traffic flow prediction. …”
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Microwave Brain Lesion Detection and Localization Using Classification Algorithms by H. Şahintürk, R. Kıymaz, B. Aslanyürek, H.G. Süngülü

“…Among these, the models trained with stochastic gradient descent classifier, ridge classifier, and logistic regression demonstrated notable accuracy (91%, 82%, and 77%, respectively) for both detection and localization of lesions.…”
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RADNet: Adaptive Spatial-Dilation Learning for Efficient Road Crack Detection by Kehao Du, Yifan Dai

“…Ablation studies show that the integration of ASDown and C2f-MSD significantly enhances both detection accuracy and computational efficiency, improving mAP50 by 5.6% over the YOLOv8n baseline while reducing computational complexity.…”
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DOE: a dynamic object elimination scheme based on geometric and semantic constraints by Yanli Liu, Siyi Chen, Heng Zhang, Neal N. Xiong, Wei Liang

“…Firstly, we employ a lightweight YOLO-Tiny network to enhance both detection accuracy and system speed. Secondly, we integrate the YOLO-Tiny network into the ORB-SLAM3 system to extract semantic information from the images and initiate the elimination of dynamic feature points. …”
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