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

“…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. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”

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

“…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. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”

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

“…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. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”

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

“…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. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”

DyHead Structure. by Zhongjian Xie (4633099)

“…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. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”

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

“…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. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”

Structure of GSConv network. by Zhongjian Xie (4633099)

“…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. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”

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

“…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. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”

Improved model distillation structure. by Zhongjian Xie (4633099)

“…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. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”

Overexpression of DNAJA4, CRYAB or DNAJB1 reduces HBx expression in HepG2 cells. by Qian Qiu (331716)

Surgical changes through ISIW implantation. by Sayaka Kimura-Uchida (22793666)

“…Pre- and postoperative data are compared by Tukey’s HSD test and asterisks mean statistical significance (p < 0.05). IOP decreases significantly from 3 to 12 months after surgery whereas GMS decreases from one day to 12 months after surgery. …”

Numbers of nuclei and centrioles per cell. by Yang-In Yim (324355)

“…Note that the values in (D) for HSET KD and combined KD of Myo10 KD and HSET, while significantly different from the control, represent decreases in centriole number, not increases (these decreases may be due to the anti-proliferative effects of HSET KD). …”

Functional and strength parameters. by Susanne S. Rauh (21192252)

“…An overall tendency to an increase in FF and a decrease in functional measures were observed over 2 years. …”

Prediction performance of each model. by Ahmed S. Alkhalifah (20721713)

“…Nonsurvivors had a significantly higher time-weighted average MP (TWA-MP) than survivors. …”

Patient inclusion flow chart. by Ahmed S. Alkhalifah (20721713)

“…Nonsurvivors had a significantly higher time-weighted average MP (TWA-MP) than survivors. …”

Prediction plots showing (A) the increase of the rodent flea abundance was mostly likely influenced by species identity: <i>Xenopsylla brasilliensis, Pulex irritans</i>, and <i>Din... by Stella T. Kessy (18700173)

Characteristics of the study population. by Alexander Ritter (21982738)

“…Psychological assessment revealed that emotional distress and level of concern significantly differed across resilience levels and categories of CT findings. …”

Follow up costs for incidental findings. by Alexander Ritter (21982738)

“…Psychological assessment revealed that emotional distress and level of concern significantly differed across resilience levels and categories of CT findings. …”

Transcriptomic data of mature adipocytes from Dbc1 KO vs WT mice by Leonardo Santos (477304)

“…<b>(D)</b> Emapplot of the top 50 significantly enriched Gene Ontology terms (Biological Process), with increased terms in red and decreased terms in blue, in Dbc1 KO compared to Dbc1^LoxP/LoxP. …”

Mutation of 1G05 epitope glycan sites impacts avidity. by Zachary T. Berndsen (9230176)