Search alternatives:
somatic decrease » small decrease (Expand Search)
dramatic » aromatic (Expand Search)
somatic decrease » small decrease (Expand Search)
dramatic » aromatic (Expand Search)
-
241
The proposed method work-flow.
Published 2025“…For example, the deep neural network model shows a decrease in RMSE from 0.926 to 0.375, MAE from 0.337 to 0.196, and MAPE from 134.63 to 114.71. …”
-
242
-
243
Histogram of the extracted parameters.
Published 2025“…Firstly, the aorta was segmented automatically by TotalSegmentator and its centerline was extracted. …”
-
244
-
245
-
246
-
247
-
248
-
249
A novel RNN architecture to improve the precision of ship trajectory predictions
Published 2025“…This research proposes a new RNN architecture that decreases the prediction error up to 50% for cargo vessels when compared to the OU model. …”
-
250
-
251
Mechanically Robust and Biodegradable Electrospun Membranes Made from Bioderived Thermoplastic Polyurethane and Polylactic Acid
Published 2024“…Blending TPU with PLA dramatically increases the strain at break of the PLA membrane, while the addition of PLA in TPU stiffens the material considerably. …”
-
252
-
253
-
254
HG module schematic.
Published 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.…”
-
255
Label data volume and label distribution.
Published 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.…”
-
256
The structure of the context guided block.
Published 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.…”
-
257
SEnet module.
Published 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.…”
-
258
AC-LayeringNetV2 architecture module.
Published 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.…”
-
259
Cracks included in the dataset.
Published 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.…”
-
260
Loss function comparison plot.
Published 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.…”