Modulation of performance during learning. by Daniel Ramandi (10047543)

N-back learning effects. by Ana María Triana (19819446)

RMSE versus learning rate. by Zhe Hu (787283)

Deep reinforcement learning agents trained using a curriculum solve navigation tasks with delayed rewards. by William L. Tong (22238845)

“…C: ADP outperforms INC and RAND (each teacher-student interaction is a step). The agent does not learn the task without a curriculum. …”

Evaluating the effectiveness of safety countermeasures at highway–railway grade crossing based on a machine learning framework by Mohammadali Zayandehroodi (19746176)

Confusion Matrix with a Description of the 4 Quadrants for Our Case. by Mudhafar Jalil Jassim Ghrabat (22177655)

Relation of the changes in Y Sway Amplitude and LFS induced by postural training with those in 95% Area. by Cristina Dolciotti (16317330)

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

Between-group differences in 95% Area, Y Sway Amplitude and LFS during postural training. by Cristina Dolciotti (16317330)

Time course of Path Length, LFS and Velocity during postural training. by Cristina Dolciotti (16317330)

Relation between training-related changes in unipedal and bipedal stance. by Cristina Dolciotti (16317330)

Time course of 95% Area, X and Y Amplitude Sway during postural training. 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)

DDX5 and DDX17 decrease viral gene expression during KSHV lytic reactivation in iSLK.219 cells. by Praneet Kaur Sandhu (21156149)

Imbalanced Dataset Distribution. by Mudhafar Jalil Jassim Ghrabat (22177655)

“…Timely identification is essential for enhancing patient results and decreasing fatality rates. Utilizing computer-assisted detection and diagnosis early on may greatly improve the chances of recovery by accurately predicting outcomes and developing suitable treatment plans. …”

Data Preprocessing Steps for IDC Dataset. by Mudhafar Jalil Jassim Ghrabat (22177655)

“…Timely identification is essential for enhancing patient results and decreasing fatality rates. Utilizing computer-assisted detection and diagnosis early on may greatly improve the chances of recovery by accurately predicting outcomes and developing suitable treatment plans. …”

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

“…Timely identification is essential for enhancing patient results and decreasing fatality rates. Utilizing computer-assisted detection and diagnosis early on may greatly improve the chances of recovery by accurately predicting outcomes and developing suitable treatment plans. …”

IDC Breast Cancer Dataset Descriptions. by Mudhafar Jalil Jassim Ghrabat (22177655)

“…Timely identification is essential for enhancing patient results and decreasing fatality rates. Utilizing computer-assisted detection and diagnosis early on may greatly improve the chances of recovery by accurately predicting outcomes and developing suitable treatment plans. …”

Accuracy Graph. by Mudhafar Jalil Jassim Ghrabat (22177655)

“…Timely identification is essential for enhancing patient results and decreasing fatality rates. Utilizing computer-assisted detection and diagnosis early on may greatly improve the chances of recovery by accurately predicting outcomes and developing suitable treatment plans. …”