3D Gaussian Splatting Methods for Real-World Scenarios by I. Petrovska, B. Jutzi

“…Just behind MVS, the original 3DGS implementation achieves second best accuracy results outperforming NeRFs in both scenarios, making it the most accurate 3DGS method. 3DGS-MCMC achieves the best and third best completeness for each scenario respectively, making it competitive with MVS and NeRFs in real-world setting. …”
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Landslide Detection in Long-Term and Low-Coherence Scenario Using Faster Intermittent Stacking InSAR Method by Huayan Dai, Lixin Wu, Yunping Liao, Lichuan Chen, Yong Yang

“…This often leads to the minimal capability of conventional time-series InSAR methods, which poses challenges for effective ground deformation detection, particularly in low-coherence areas over long-term scenarios. …”
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Population control methods in stochastic extinction and outbreak scenarios. by Juan Segura, Frank M Hilker, Daniel Franco

“…Moreover, there is a clear disparity between the two control methods: in the extinction scenarios, ALC can be effective and ATH can be counterproductive, whereas in the outbreak scenarios the situation is reversed, with ATH being effective and ALC being potentially counterproductive.…”
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Optimal Configuration of ESS in Distribution Network Considering Generation of PV-Load Time Series Scenarios by Xiaolong Xiao, Mingming Shi, Fan Wu, Yukai Wei, Bo Zhao, Fang Zhang

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Crack Detection in Civil Infrastructure: A Method-Scenario Review by Chang Haochen, Gu Weifan, Guo Baohua, Bassir David

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Deepfake Dilemmas: Imagine Tomorrow’s Surveillance Society through Three Scenarios by Fatma Doğan Akkaya

“…Moving beyond technical considerations, the research employs social prediction methods to explore three potential future scenarios involving deepfake avatars: seamless integration that facilitates self-expression but complicates digital identity control; pervasive algorithmic surveillance that exacerbates social control and privacy issues; and the concept of ghost avatars, that is, digital representations that function as commodities or tools of resistance. …”
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Lightweight Detection Methods for Multi-Scale Targets in Complex Scenarios by Anjun Yu, Zhichao Rao, Yonghua Xiong, Jinhua She

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Digital Simulation Test Method for Multiple Scenarios Relay Protection by Qingquan LIU, Peng YANG, Tiecheng LI, Xianzhi WANG, Minghao WEN

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Analysis and Selection Method for Radar Echo Features in Challenging Scenarios by Yunlong Dong, Xiao Luo, Hao Ding, Ningbo Liu, Zheng Cao

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Visual information processing characteristics of tactical decisions of soccer players in 3V3 offense scenarios by Tianyu Gao, Peng Shi, Duoyao Zhang, Guodong Wang, Jianming Zhang

“…Real match 3V3 offensive tactical scenarios were used as stimulus materials. …”
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RGB-T Object Detection With Failure Scenarios by Qingwang Wang, Yuxuan Sun, Yongke Chi, Tao Shen

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A network intrusion detection method designed for few-shot scenarios by Weichen HU, Congyuan XU, Yong ZHAN, Guanghui CHEN, Siqing LIU, Zhiqiang WANG, Xiaolin WANG

“…Existing intrusion detection techniques often require numerous malicious samples for model training.However, in real-world scenarios, only a small number of intrusion traffic samples can be obtained, which belong to few-shot scenarios.To address this challenge, a network intrusion detection method designed for few-shot scenarios was proposed.The method comprised two main parts: a packet sampling module and a meta-learning module.The packet sampling module was used for filtering, segmenting, and recombining raw network data, while the meta-learning module was used for feature extraction and result classification.Experimental results based on three few-shot datasets constructed from real network traffic data sources show that the method exhibits good applicability and fast convergence and effectively reduces the occurrence of outliers.In the case of 10 training samples, the maximum achievable detection rate is 99.29%, while the accuracy rate can reach a maximum of 97.93%.These findings demonstrate a noticeable improvement of 0.12% and 0.37% respectively, in comparison to existing algorithms.…”
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The methods of scenario designing for the development of regional systems of vocational education and training by V. I. Blinov, A. I. Satdykov, I. S. Sergeev, N. F. Rodichev

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A soft-linking method for responsive modelling of decarbonisation scenario costs by Ché Cameron, Aoife Foley, Henrik Lund, Seán McLoone

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Reproduction of Staff of IT-Branch. Scenario Analysis by E. V. Vasileva

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UPBD: Construction and Evaluation Methods of the Underwater Polarization Benchmark Dataset for Complex Scenarios by Haihong Jin, Shangle Yao, Hao Yao, Wenjie Zhang, Zhiguo Fan

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SDGTrack: A Multi-Target Tracking Method for Pigs in Multiple Farming Scenarios by Tao Liu, Dengfei Jie, Junwei Zhuang, Dehui Zhang, Jincheng He

“…The experimental results demonstrate that SDGTrack achieved a MOTA score of 80.9%, an IDSW of 24, and an IDF1 score of 85.1% across various scenarios. Compared to the original CSTrack method, SDGTrack improved the MOTA and IDF1 scores by 16.7% and 33.3%, respectively, while significantly reducing the number of ID switches by 94.6%. …”
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Scenario Method of Strategic Planning and Forecasting the Development of the Rural Economy in Agricultural Complex by Milyausha T. Lukyanova, Vitaliy A. Kovshov, Zagir A. Galin, Zariya A. Zalilova, Eugene V. Stovba

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An autonomous vehicles’ test case extraction method: Example of vehicle-to-pedestrian scenarios by Zhengping Tan, Qian Wang, Wenhao Hu, Pingfei Li, Liangliang Shi, Hao Feng

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Complexity Evaluation for Urban Intersection Scenarios in Autonomous Driving Tests: Method and Validation by Jiangkun Li, Ruixue Zong, Ying Wang, Weiwen Deng

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