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

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

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

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

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

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

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

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

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

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

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

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

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

Thesis-RAMIS-Figs_Slides حسب Felipe Santibañez-Leal (10967991)

"…In this direction, the option of estimating the statistics of the model directly from the training image (performing a refined pattern search instead of simulating data) is a very promising.<br><br>Finally, although the developed concepts, ideas and algorithms have been developed for inverse problems in geostatistics, the results are applicable to a wide range of disciplines where similar sampling problems need to be faced, included but not limited to design of communication networks, optimal integration and communication of swarms of robots and drones, remote sensing.…"

Flowchart scheme of the ML-based model. حسب Noshaba Qasmi (20405009)

Data_Sheet_1_A real-time driver fatigue identification method based on GA-GRNN.ZIP حسب Xiaoyuan Wang (492534)

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

Models and Dataset حسب M RN (9866504)

"…The algorithm does not rely on predefined control parameters like crossover or mutation rates, which makes it lightweight and easy to implement for various feature selection and optimization tasks.…"