Future works

from Urban Scene Segmentation for Autonomous Vehicles using Multi-Domain Adaptation

Problem Statement

 We recommend trying the same framework on other domains [real urban datasets].

 Try with another base model such as Deep lap V3, ProDA ,

 Or with another faster base model architecture, to be replaced the Deep lab version-2 even the model is less accuracy but will be Faster, and to be tested on the both models: baseline, and MTKT.

 Impalement Different Deep Reinforcement learning algorithms such as the

Actor-Critic and Game-GAN, and utilize the parallel processing.

Future works

Next Article

Problem Statement

More articles from this publication:

Problem Statement

Datasets

Literature and old Trials

Results

Methodology

Introduction

Deployment

Deep Reinforcement Learning – DQN in Carla

References

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Urban Scene Segmentation for Autonomous Vehicles using Multi-Domain Adaptation