Intraoperative facial and intraoral photographs of the case with mandibular third molar extraction. by Lijuan Liu (136685)

Third. by Cuicui Liu (1496260)

Posttreatment facial, intraoral photographs, and radiographs of the case with mandibular third molar extraction. by Lijuan Liu (136685)

Pretreatment facial, intraoral photographs, and radiographs of the case with mandibular third molar extraction. by Lijuan Liu (136685)

Superimposition of the cephalometric tracings obtained before and after treatment of case with mandibular third molar extraction. by Lijuan Liu (136685)

Comparison of pretreatment cephalometric variables between premolar extraction and mandibular third molar extraction groups. by Lijuan Liu (136685)

Comparison of upper and lower arch crowding between premolar extraction group and the mandibular third molar extraction groups. by Lijuan Liu (136685)

Comparison of treatment effects between premolar extraction and mandibular third molar extraction groups. * p < 0.05; ** p < 0.01. by Lijuan Liu (136685)

Dynamics of net spillage in the third stage (post epidemic). by Cuicui Liu (1496260)

CNN Model Architecture. by Mudhafar Jalil Jassim Ghrabat (22177655)

Subjects:

Changes in total spillage during the third stage (post epidemic). by Cuicui Liu (1496260)

Flowchart of Proposed SMO_CNN. by Mudhafar Jalil Jassim Ghrabat (22177655)

Subjects:

CNN Model Layers Summary. by Mudhafar Jalil Jassim Ghrabat (22177655)

Subjects:

Training-induced changes in bipedal stance. by Cristina Dolciotti (16317330)

Consolidation of training-induced changes in unipedal stance: 95% Area, Y Sway Amplitude and LFS. by Cristina Dolciotti (16317330)

Consolidation of training-induced changes in unipedal stance: Path Length, X Sway Amplitude and Velocity. by Cristina Dolciotti (16317330)

Dynamics of pairwise net spillovers between sectors in the third stage (post epidemic). by Cuicui Liu (1496260)

Performance Results of Proposed SMO_CNN Model. by Mudhafar Jalil Jassim Ghrabat (22177655)

Subjects:

Validation of child labor measures using third-party data, households with all children in school. by Guilherme Lichand (11410286)

CNN framework. by Sajid Mehmood (6689843)

“…We propose to implement both MLP (Multilayer Perceptron) and CNN (Convolutional Neural Networks) based on conventional methods to detect the Denial of Services (DDoS) attack. …”