A Monte Carlo Search-Based Triplet Sampling Method For Learning Disentangled Representation Of Impulsive Noise On Steering Gear

This video program is a part of the Premium package:

A Monte Carlo Search-Based Triplet Sampling Method For Learning Disentangled Representation Of Impulsive Noise On Steering Gear


  • IEEE MemberUS $11.00
  • Society MemberUS $0.00
  • IEEE Student MemberUS $11.00
  • Non-IEEE MemberUS $15.00
Purchase

A Monte Carlo Search-Based Triplet Sampling Method For Learning Disentangled Representation Of Impulsive Noise On Steering Gear

0 views
  • Share
Create Account or Sign In to post comments
The classification task of impact noise on vehicle steering system mainly addresses the issue of modeling the transient and impulsive nature. Though various deep learning models including triplet network have been developed, the existing triplet network b
The classification task of impact noise on vehicle steering system mainly addresses the issue of modeling the transient and impulsive nature. Though various deep learning models including triplet network have been developed, the existing triplet network b