View RSS Feed

newdigital

Neural networks made easy (Part 72): Trajectory prediction in noisy environments

Rate this Entry
by , 06-06-2024 at 10:09 AM (212 Views)
      
   
The noise prediction module solves the auxiliary problem of identifying noise in the analyzed trajectories. This helps the movement prediction model better model potential spatial diversity and improves understanding of the underlying representation in movement prediction, thereby improving future predictions.
The authors of the method conducted additional experiments to empirically demonstrate the critical importance of the spatial consistency and noise prediction modules for SSWNP. When using only the spatial consistency module to solve the movement prediction problem, suboptimal performance of the trained model is observed. Therefore, they integrate both modules in their work.
more...

Submit "Neural networks made easy (Part 72): Trajectory prediction in noisy environments" to Google Submit "Neural networks made easy (Part 72): Trajectory prediction in noisy environments" to del.icio.us Submit "Neural networks made easy (Part 72): Trajectory prediction in noisy environments" to Digg Submit "Neural networks made easy (Part 72): Trajectory prediction in noisy environments" to reddit

Tags: None Add / Edit Tags
Categories
Uncategorized

Comments