The improved CSW-YOLO model framework. حسب Qian Shen (89639)

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Thermodynamic diagram visualization results after adding the LSKA attention mechanism. حسب Qian Shen (89639)

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Visualization result of yolov8 heatmap. حسب Qian Shen (89639)

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Traffic sign detection results of TT100K. حسب Qian Shen (89639)

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Block diagram of PConv and FasterNetBlock modules. حسب Qian Shen (89639)

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The detection accuracy of each ablation experiment. حسب Qian Shen (89639)

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Traffic sign detection results of CCTSDB 2021. حسب Qian Shen (89639)

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The FEM mesh model for the three-layer case, where 7919 degrees of freedom are used. حسب Xiaogang Li (299205)

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The RMT diagram for an acoustic coating with three-layer periodic inclusions, in which the start (10 Hz, blue dots) and cut-off (10000 Hz, black asterisks) frequencies of sound abs... حسب Xiaogang Li (299205)

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The influence of different materials of scatterers on the sound absorption. حسب Xiaogang Li (299205)

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Data for Figs 3–9. حسب Xiaogang Li (299205)

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The solid material attributes. حسب Xiaogang Li (299205)

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Sound absorption spectrum calculated by TMM (dots) and FEM (solid lines). حسب Xiaogang Li (299205)

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Fig 6 - حسب Xiaogang Li (299205)

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Simulation sample. حسب Xiaogang Li (299205)

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Fig 7 - حسب Xiaogang Li (299205)

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The normalized acoustic resistance (blue lines) and reactance (red dotted lines) of the optimization case in Fig 7. حسب Xiaogang Li (299205)

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Cross section of the metagrating and the distribution of effective homogeneous layers. حسب Xiaogang Li (299205)

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Data and code from: AI-based image profiling and detection for the beetle byte quintet using Vision Transformer (ViT) in advanced stored product infestation monitoring حسب Alison Gerken (17362585)

Model’s measure methods. حسب Songsong Wang (8088293)

"…The findings indicate that the LSTM model, when integrated with the watershed-internal KG and LLM, can effectively incorporate critical elements influencing water level changes, the accuracy of the LLM-KG-LSTM model is enhanced by 3% compared to the standard LSTM model, and the LSTM series outperforms both RNN and GRU models, Our method will guide future research from the perspective of focusing on forecasting algorithms to the perspective of focusing on the relationship between multi-dimensional disaster data and algorithm parallelism.…"