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complement control » complementary control (Expand Search), coherent control (Expand Search)
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level coding » level according (Expand Search), level modeling (Expand Search), level using (Expand Search)
elements wt » elements _ (Expand Search), elements b (Expand Search), elements fe (Expand Search)
complement control » complementary control (Expand Search), coherent control (Expand Search)
coding algorithm » cosine algorithm (Expand Search), modeling algorithm (Expand Search), finding algorithm (Expand Search)
wt algorithm » _ algorithm (Expand Search), ii algorithm (Expand Search), rf algorithm (Expand Search)
level coding » level according (Expand Search), level modeling (Expand Search), level using (Expand Search)
elements wt » elements _ (Expand Search), elements b (Expand Search), elements fe (Expand Search)
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<b>BRISC: Annotated Dataset for Brain Tumor Segmentation and Classification</b>
Published 2025“…It provides high-quality, physician-validated pixel-level masks and a balanced multi-class classification split, suitable for benchmarking segmentation and classification algorithms as well as multi-task learning research.…”
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Range of point clouds.
Published 2025“…On the KITTI dataset, our algorithm achieved 3D average detection accuracy (AP3D) of 81.15%, 62.02%, and 58.68% across three difficulty levels. …”
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185
Results of ablation experiment.
Published 2025“…On the KITTI dataset, our algorithm achieved 3D average detection accuracy (AP3D) of 81.15%, 62.02%, and 58.68% across three difficulty levels. …”
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186
Transformer Encoder network structure.
Published 2025“…On the KITTI dataset, our algorithm achieved 3D average detection accuracy (AP3D) of 81.15%, 62.02%, and 58.68% across three difficulty levels. …”
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187
Line chart of frame rate.
Published 2025“…On the KITTI dataset, our algorithm achieved 3D average detection accuracy (AP3D) of 81.15%, 62.02%, and 58.68% across three difficulty levels. …”
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188
The total loss and three-component loss.
Published 2025“…On the KITTI dataset, our algorithm achieved 3D average detection accuracy (AP3D) of 81.15%, 62.02%, and 58.68% across three difficulty levels. …”
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189
Improved upsampling module based on Transformer.
Published 2025“…On the KITTI dataset, our algorithm achieved 3D average detection accuracy (AP3D) of 81.15%, 62.02%, and 58.68% across three difficulty levels. …”
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Overall framework design.
Published 2025“…Our approach uses cross-project code clone detection to establish the ground truth for software reuse, identifying code clones across popular GitHub projects as indicators of potential reuse candidates. …”
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198
Gamma distribution of reuse.
Published 2025“…Our approach uses cross-project code clone detection to establish the ground truth for software reuse, identifying code clones across popular GitHub projects as indicators of potential reuse candidates. …”
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Top 5 correlated features based on reuse.
Published 2025“…Our approach uses cross-project code clone detection to establish the ground truth for software reuse, identifying code clones across popular GitHub projects as indicators of potential reuse candidates. …”
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Features with the top importance score.
Published 2025“…Our approach uses cross-project code clone detection to establish the ground truth for software reuse, identifying code clones across popular GitHub projects as indicators of potential reuse candidates. …”