Latent state estimations for experimental data with time limit for subject 20. by Samiul Alam (18563323)

Latent state estimations for experimental data with time limit for subject 5. by Samiul Alam (18563323)

Latent state estimations for experimental data with time limit for subject 21. by Samiul Alam (18563323)

Latent state estimations for experimental data with time limit for subject 7. by Samiul Alam (18563323)

Latent state estimations for experimental data with time limit for subject 3. by Samiul Alam (18563323)

Latent state estimations for experimental data with time limit for subject 22. by Samiul Alam (18563323)

Latent state estimations for experimental data with time limit for subject 4. by Samiul Alam (18563323)

Latent state estimations for experimental data with time limit for subject 19. by Samiul Alam (18563323)

Latent state estimations for experimental data with time limit for subject 10. by Samiul Alam (18563323)

Latent state estimations for experimental data with time limit for subject 18. by Samiul Alam (18563323)

Latent state estimations for experimental data with time limit for subject 8. by Samiul Alam (18563323)

Latent state estimations for experimental data with time limit for subject 6. by Samiul Alam (18563323)

Latent state estimations for experimental data with time limit for subject 1. by Samiul Alam (18563323)

Latent state estimations for experimental data with time limit for subject 15. by Samiul Alam (18563323)

Latent state estimations for experimental data with time limit for subject 9. by Samiul Alam (18563323)

Latent state estimations for experimental data with time limit for subject 12. by Samiul Alam (18563323)

Latent state estimations for experimental data with time limit for subject 2. by Samiul Alam (18563323)

PathOlOgics_RBCs Python Scripts.zip by Ahmed Elsafty (16943883)

“…</p><p dir="ltr">In terms of classification, a second algorithm was developed and employed to preliminary sort or group the individual cells (after excluding the overlapping cells manually) into different categories using five geometric measurements applied to the extracted contour from each binary image mask (see PathOlOgics_script_2; preliminary shape measurements). …”

Presentation_1_Modified GAN Augmentation Algorithms for the MRI-Classification of Myocardial Scar Tissue in Ischemic Cardiomyopathy.PPTX by Umesh C. Sharma (10785063)

“…Currently, there are no optimized deep-learning algorithms for the automated classification of scarred vs. normal myocardium. …”

Data_Sheet_1_Multiclass Classification Based on Combined Motor Imageries.pdf by Cecilia Lindig-León (7889777)