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.…”

Backbone comparison in crack detection. 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.…”

Statistical analysis table for ablation tests. 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.…”

Summary of false positives and false negatives. 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.…”

PR parameter comparison chart. 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.…”

RAK-Conv. 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.…”

Structure of YOLOv8n. 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.…”

Accommodating talker variability in noise (Zhang & Peng, 2025) by Kaile Zhang (21763791)

“…Attentional control plays a crucial role in facilitating extrinsic normalization in specific noise conditions.…”

PsyCap and its four components. by Yin Ru SHI (19762198)

“…ANOVA results suggested that teachers showed a significant increase in their PsyCap scores after completing the training, although the training effect slightly decreased after one week. …”

S1 Data - by Yin Ru SHI (19762198)

“…ANOVA results suggested that teachers showed a significant increase in their PsyCap scores after completing the training, although the training effect slightly decreased after one week. …”

Characteristics of children in the study. by Shijie Yu (511369)

“…These findings highlight that governments and society should pay attention to the HRQOL of myopic children.</p></div>…”

Network effects of DLPFC-tDCS protocols with different stimulation duration. by Yanqing Dong (8829548)

Impact of structural connectivity on dynamic functional connectivity in stimulated regions in right DLPFC-tDCS protocol (F4a-Fp1c). by Yanqing Dong (8829548)

Dynamic functional connectivity changes in left DLPFC-tDCS protocol (F3a-Fp2c). by Yanqing Dong (8829548)

Dynamic network effects of right DLPFC-tDCS protocol (F4a-Fp1c). by Yanqing Dong (8829548)

Impact of structural connectivity on dynamic functional connectivity associated with the stimulated regions in left DLPFC-tDCS protocol (F3a-Fp2c). by Yanqing Dong (8829548)

Dynamic network effects of left DLPFC-tDCS protocol (F3a-Fp2c) with the stimulation duration of 120s (168 TRs). by Yanqing Dong (8829548)

Dynamic network effects of left DLPFC-tDCS protocol (F3a-Fp2c) with the stimulation duration of 90s (125 TRs). by Yanqing Dong (8829548)