The variables used and equations. by Hoang Thanh Nhon (22311837)

“…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. …”

An illustration of how RF works. by Hoang Thanh Nhon (22311837)

“…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. …”

The proposed method work-flow. by Hoang Thanh Nhon (22311837)

“…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. …”

Histogram of the extracted parameters. by Qiuyu Du (20760848)

“…Firstly, the aorta was segmented automatically by TotalSegmentator and its centerline was extracted. …”

DA-9601 reduced Iba-1 expression. by Mijung Lee (397790)

Evaluation of PCR amplification bias and PCR amplification efficiency. by Trang Thi Quynh Tran (20485595)

A novel RNN architecture to improve the precision of ship trajectory predictions by Martha Dais Ferreira (18704596)

“…This research proposes a new RNN architecture that decreases the prediction error up to 50% for cargo vessels when compared to the OU model. …”

Weak magnetic fields disturb cytoskeleton reassembly after nocodazole exposure, and influence actin polymerization. by Abasalt Bahrami (21989867)

Mechanically Robust and Biodegradable Electrospun Membranes Made from Bioderived Thermoplastic Polyurethane and Polylactic Acid by Robert J. Chambers (19856799)

“…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. …”

Augmented oxycodone intake in 16-h vs 4-h sessions. by Burt M. Sharp (20854686)

HG module schematic. by Wenhao Ren (2561731)

“…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.…”

Label data volume and label distribution. by Wenhao Ren (2561731)

“…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.…”

The structure of the context guided block. by Wenhao Ren (2561731)

“…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.…”

SEnet module. by Wenhao Ren (2561731)

“…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.…”

AC-LayeringNetV2 architecture module. by Wenhao Ren (2561731)

“…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.…”

Cracks included in the dataset. by Wenhao Ren (2561731)

“…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.…”

Loss function comparison plot. by Wenhao Ren (2561731)

“…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.…”

Edge device performance benchmarking. by Wenhao Ren (2561731)

“…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.…”

Typical error cases. by Wenhao Ren (2561731)

“…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.…”

Computational efficiency comparison. by Wenhao Ren (2561731)

“…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.…”