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modeling algorithm » making algorithm (Expand Search)
mapping algorithm » making algorithm (Expand Search), mining algorithm (Expand Search), learning algorithm (Expand Search)
element mapping » elemental mapping (Expand Search), element modeling (Expand Search), argument mapping (Expand Search)
data modeling » data modelling (Expand Search), data models (Expand Search)
element based » engagement based (Expand Search)
modeling algorithm » making algorithm (Expand Search)
mapping algorithm » making algorithm (Expand Search), mining algorithm (Expand Search), learning algorithm (Expand Search)
element mapping » elemental mapping (Expand Search), element modeling (Expand Search), argument mapping (Expand Search)
data modeling » data modelling (Expand Search), data models (Expand Search)
element based » engagement based (Expand Search)
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Model-Based Clustering of Categorical Data Based on the Hamming Distance
Published 2024“…<p>A model-based approach is developed for clustering categorical data with no natural ordering. …”
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Risk element category diagram.
Published 2025“…It can be summarized that the algorithmic model has good accuracy and robustness. …”
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Comparison of mAP curves in ablation experiments.
Published 2025“…Compared to the original YOLOv8 model, the improved algorithm shows increases of 2.2% in precision, 0.6% in recall, and 2.0% in mAP@0.5, with a detection speed improvement of 65.48 FPS. …”
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Video 1_A hybrid elastic-hyperelastic approach for simulating soft tactile sensors.mp4
Published 2025“…A significant challenge for simulating tactile sensors is balancing the trade-off between accuracy and processing time in simulation algorithms and models. To address this, we propose a hybrid approach that combines elastic and hyperelastic finite element simulations, complemented by convolutional neural networks (CNNs), to generate synthetic tactile maps of a soft capacitive tactile sensor. …”
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Scatter diagram of different principal elements.
Published 2025“…The experimental results show that the SSA-LightGBM model proposed in this paper has an average fault diagnosis accuracy of 93.6% after SSA algorithm optimization, which is 3.6% higher than before optimization. …”
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YOLOv8 model architecture diagram.
Published 2025“…Compared to the original YOLOv8 model, the improved algorithm shows increases of 2.2% in precision, 0.6% in recall, and 2.0% in mAP@0.5, with a detection speed improvement of 65.48 FPS. …”
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