Comparison experiment of accuracy improvement. by Zhongjian Xie (4633099)

“…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. …”

Comparison of different pruning rates. by Zhongjian Xie (4633099)

“…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. …”

Comparison of experimental results at ablation. by Zhongjian Xie (4633099)

“…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. …”

Result of comparison of different lightweight. by Zhongjian Xie (4633099)

“…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. …”

DyHead Structure. by Zhongjian Xie (4633099)

“…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. …”

The parameters of the training phase. by Zhongjian Xie (4633099)

“…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. …”

Structure of GSConv network. by Zhongjian Xie (4633099)

“…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. …”

Comparison experiment of accuracy improvement. by Zhongjian Xie (4633099)

“…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. …”

Improved model distillation structure. by Zhongjian Xie (4633099)

“…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. …”

Highest posterior density (HPD) of the posterior genotypic main effects (A), probability of superior performance across environments (B), and probability of superior stability acro... by Mohammadreza Shiri (10368554)

ATPase activity of Pns10 does not contribute to mitochondrial energy impairment or ROS accumulation in Sf9 cells. by Lianshun Zheng (22086585)

Effect of <i>Rps</i> lectins on the bacterial extracellular matrix. by Mariama D. Carter (19727487)

Presentation_1_Multifaceted neuroprotective approach of Trolox in Alzheimer's disease mouse model: targeting Aβ pathology, neuroinflammation, oxidative stress, and synaptic dysfunc... by Muhammad Tahir (741682)

“…This research study is significant as it aims to assess the neuroprotective properties of vitamin E (VE) analog Trolox in an Aβ_{1 − 42}-induced AD mouse model. …”

Distribution of samples according to the geographic origin of the infection, <i>Leishmania</i> species, and LRV1 statutes. by Fredy A. Pazmiño (20613765)

Ignition delay process shot by high-speed camera. by Lei Bai (631944)

“…The evolution of the fractal dimension of the lubricating oil droplet flame shows a trend of first increasing and then slowly decreasing. …”

Data disclosure (Bai - manuscript). by Lei Bai (631944)

“…The evolution of the fractal dimension of the lubricating oil droplet flame shows a trend of first increasing and then slowly decreasing. …”

Experimental bench and corresponding facility. by Lei Bai (631944)

“…The evolution of the fractal dimension of the lubricating oil droplet flame shows a trend of first increasing and then slowly decreasing. …”

Three classic combustion stages of the flame. by Lei Bai (631944)

“…The evolution of the fractal dimension of the lubricating oil droplet flame shows a trend of first increasing and then slowly decreasing. …”

Flame binarization image processing flow. by Lei Bai (631944)

“…The evolution of the fractal dimension of the lubricating oil droplet flame shows a trend of first increasing and then slowly decreasing. …”

Experimental condition of fixed oil drop volume. by Lei Bai (631944)

“…The evolution of the fractal dimension of the lubricating oil droplet flame shows a trend of first increasing and then slowly decreasing. …”