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Titlebook: Industrial Control Systems Security and Resiliency; Practice and Theory Craig Rieger,Indrajit Ray,Michael A. Haney Book 2019 Springer Natur

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發(fā)表于 2025-3-23 13:15:00 | 只看該作者
https://doi.org/10.1007/978-3-030-18214-4ICS; SCADA; DCS; PLC; cyber threats; resilient design; network security; intrusion detection; malware; operat
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發(fā)表于 2025-3-23 15:12:46 | 只看該作者
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發(fā)表于 2025-3-23 19:54:20 | 只看該作者
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發(fā)表于 2025-3-24 01:49:20 | 只看該作者
tains multiple distances as well as in-plane and out-of plane rotations. The high accuracy of the classification results indicate the descriptive yet compact nature of our texture representation, and demonstrates the importance of geometric texture analysis, pointing the way towards improvements in
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發(fā)表于 2025-3-24 02:37:07 | 只看該作者
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發(fā)表于 2025-3-24 09:29:13 | 只看該作者
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發(fā)表于 2025-3-24 12:59:48 | 只看該作者
Curtis St. Michel,Sarah Freemans and object detection on color images, respectively. To evaluate the benefit of joining color and depth information of multiple cameras, we recorded a novel dataset with four Kinects showing significant improvements over a DPM baseline for 9 object classes aggregated in challenging scenes. In contr
18#
發(fā)表于 2025-3-24 18:42:32 | 只看該作者
Kinect SDK to analyze the motion patterns and anthropometric features over the entire track sequence. We show the proposed method can identify people that perform different actions (e.g. walk and run) with varying levels of complexity. When compared to a state-of-the-art gait-based method that uses
19#
發(fā)表于 2025-3-24 21:51:30 | 只看該作者
Pengyuan Wang,Manimaran Govindarasudy modeling – nonzero coefficients are only assigned to the basis poses from a small number of pose subspaces that are close to each other in the pose-subspace hierarchy. We combine PLCR into the matching-pursuit based 3D human-pose reconstruction algorithm and show that the proposed PLCR-based algo
20#
發(fā)表于 2025-3-25 01:57:24 | 只看該作者
Mohammad Ashiqur Rahman,Ehab Al-Shaerbases have demonstrated that the FDM outperforms the state-of-the-art methods for facial expression analysis. More importantly, the FDM achieves an impressive performance in a cross-database validation, which demonstrates the generalization capability of the selected features.
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