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Edge device performance benchmarking.
منشور في 2025"…Additionally, the model achieves a 6.55% reduction in size and a 0.03% decrease in computational complexity. These results highlight the practical applicability and efficiency of the proposed approach for automatic crack detection in building structures, emphasizing the novel integration of feature fusion and attention mechanisms to address challenges in real-time and high-accuracy detection of micro-cracks in complex environments.…"
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Typical error cases.
منشور في 2025"…Additionally, the model achieves a 6.55% reduction in size and a 0.03% decrease in computational complexity. These results highlight the practical applicability and efficiency of the proposed approach for automatic crack detection in building structures, emphasizing the novel integration of feature fusion and attention mechanisms to address challenges in real-time and high-accuracy detection of micro-cracks in complex environments.…"
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263
Computational efficiency comparison.
منشور في 2025"…Additionally, the model achieves a 6.55% reduction in size and a 0.03% decrease in computational complexity. These results highlight the practical applicability and efficiency of the proposed approach for automatic crack detection in building structures, emphasizing the novel integration of feature fusion and attention mechanisms to address challenges in real-time and high-accuracy detection of micro-cracks in complex environments.…"
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Backbone comparison in crack detection.
منشور في 2025"…Additionally, the model achieves a 6.55% reduction in size and a 0.03% decrease in computational complexity. These results highlight the practical applicability and efficiency of the proposed approach for automatic crack detection in building structures, emphasizing the novel integration of feature fusion and attention mechanisms to address challenges in real-time and high-accuracy detection of micro-cracks in complex environments.…"
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Statistical analysis table for ablation tests.
منشور في 2025"…Additionally, the model achieves a 6.55% reduction in size and a 0.03% decrease in computational complexity. These results highlight the practical applicability and efficiency of the proposed approach for automatic crack detection in building structures, emphasizing the novel integration of feature fusion and attention mechanisms to address challenges in real-time and high-accuracy detection of micro-cracks in complex environments.…"
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Summary of false positives and false negatives.
منشور في 2025"…Additionally, the model achieves a 6.55% reduction in size and a 0.03% decrease in computational complexity. These results highlight the practical applicability and efficiency of the proposed approach for automatic crack detection in building structures, emphasizing the novel integration of feature fusion and attention mechanisms to address challenges in real-time and high-accuracy detection of micro-cracks in complex environments.…"
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267
PR parameter comparison chart.
منشور في 2025"…Additionally, the model achieves a 6.55% reduction in size and a 0.03% decrease in computational complexity. These results highlight the practical applicability and efficiency of the proposed approach for automatic crack detection in building structures, emphasizing the novel integration of feature fusion and attention mechanisms to address challenges in real-time and high-accuracy detection of micro-cracks in complex environments.…"
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268
RAK-Conv.
منشور في 2025"…Additionally, the model achieves a 6.55% reduction in size and a 0.03% decrease in computational complexity. These results highlight the practical applicability and efficiency of the proposed approach for automatic crack detection in building structures, emphasizing the novel integration of feature fusion and attention mechanisms to address challenges in real-time and high-accuracy detection of micro-cracks in complex environments.…"
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Structure of YOLOv8n.
منشور في 2025"…Additionally, the model achieves a 6.55% reduction in size and a 0.03% decrease in computational complexity. These results highlight the practical applicability and efficiency of the proposed approach for automatic crack detection in building structures, emphasizing the novel integration of feature fusion and attention mechanisms to address challenges in real-time and high-accuracy detection of micro-cracks in complex environments.…"
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270
Underlying data for the main figures.
منشور في 2024"…Loss of RBM-26 function causes a dramatic overexpression of <i>mals-1</i> mRNA and MALS-1 protein. …"
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271
Underlying data for the supplemental figures.
منشور في 2024"…Loss of RBM-26 function causes a dramatic overexpression of <i>mals-1</i> mRNA and MALS-1 protein. …"
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272
Room-Temperature Self-Healable Glassy Semicrystalline Polymers via Ionic Aggregations
منشور في 2024"…Semicrystalline polymers constitute the largest fraction of industrial and engineering plastics but are difficult to automatically self-heal in their glassy state due to the frozen molecular chains. …"
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273
Room-Temperature Self-Healable Glassy Semicrystalline Polymers via Ionic Aggregations
منشور في 2024"…Semicrystalline polymers constitute the largest fraction of industrial and engineering plastics but are difficult to automatically self-heal in their glassy state due to the frozen molecular chains. …"
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274
Room-Temperature Self-Healable Glassy Semicrystalline Polymers via Ionic Aggregations
منشور في 2024"…Semicrystalline polymers constitute the largest fraction of industrial and engineering plastics but are difficult to automatically self-heal in their glassy state due to the frozen molecular chains. …"
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275
Room-Temperature Self-Healable Glassy Semicrystalline Polymers via Ionic Aggregations
منشور في 2024"…Semicrystalline polymers constitute the largest fraction of industrial and engineering plastics but are difficult to automatically self-heal in their glassy state due to the frozen molecular chains. …"
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276
R project including metadata update.
منشور في 2025"…Without such amendments, the accumulation of contradictory species assignments within BINs will continue to rise and the reliability of specimen identification by BOLD will decrease.</p></div>…"
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277
Classes of errors and gaps in BOLD metadata.
منشور في 2025"…Without such amendments, the accumulation of contradictory species assignments within BINs will continue to rise and the reliability of specimen identification by BOLD will decrease.</p></div>…"
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