Search alternatives:
coding algorithm » cosine algorithm (Expand Search), modeling algorithm (Expand Search), finding algorithm (Expand Search)
complement ipca » complement 5a (Expand Search), complement c3 (Expand Search), complement c5 (Expand Search)
ipca algorithm » wgcna algorithm (Expand Search), cscap algorithm (Expand Search), ii algorithm (Expand Search)
elements modbo » element model (Expand Search)
level coding » level according (Expand Search), level modeling (Expand Search), level using (Expand Search)
coding algorithm » cosine algorithm (Expand Search), modeling algorithm (Expand Search), finding algorithm (Expand Search)
complement ipca » complement 5a (Expand Search), complement c3 (Expand Search), complement c5 (Expand Search)
ipca algorithm » wgcna algorithm (Expand Search), cscap algorithm (Expand Search), ii algorithm (Expand Search)
elements modbo » element model (Expand Search)
level coding » level according (Expand Search), level modeling (Expand Search), level using (Expand Search)
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181
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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182
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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183
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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192
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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193
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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194
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. …”
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195
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196
S1 Graphical abstract -
Published 2025“…The software uses a shape-detection algorithm to single out and track the movement of pillars’ tips for the most common shapes of EHT platforms. …”
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197
Quantitative results on WEDU dataset.
Published 2024“…In comparative experiments on four plant datasets, MAR-YOLOv9 improved the mAP@0.5 accuracy by 39.18% compared to seven mainstream object detection algorithms, and by 1.28% compared to the YOLOv9 model. …”
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198
Counting results on DRPD dataset.
Published 2024“…In comparative experiments on four plant datasets, MAR-YOLOv9 improved the mAP@0.5 accuracy by 39.18% compared to seven mainstream object detection algorithms, and by 1.28% compared to the YOLOv9 model. …”
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199
Quantitative results on RFRB dataset.
Published 2024“…In comparative experiments on four plant datasets, MAR-YOLOv9 improved the mAP@0.5 accuracy by 39.18% compared to seven mainstream object detection algorithms, and by 1.28% compared to the YOLOv9 model. …”
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200
Main module structure.
Published 2024“…In comparative experiments on four plant datasets, MAR-YOLOv9 improved the mAP@0.5 accuracy by 39.18% compared to seven mainstream object detection algorithms, and by 1.28% compared to the YOLOv9 model. …”