40 citations · 53 across the 4 of their papers we have counts for
6 papers
Rationale-aware Autonomous Driving Policy utilizing Safety Force Field implemented on CARLA Simulator
Ho Suk, Taewoo Kim, Hyungbin Park +3
Despite the rapid improvement of autonomous driving technology in recent years, automotive manufacturers must resolve liability issues to commercialize autonomous passenger car of…
A Survey on Deep Reinforcement Learning-based Approaches for Adaptation and Generalization
Pamul Yadav, Ashutosh Mishra, Junyong Lee +1
Deep Reinforcement Learning (DRL) aims to create intelligent agents that can learn to solve complex problems efficiently in a real-world environment. Typically, two learning goals:…
TMA: Tera-MACs/W Neural Hardware Inference Accelerator with a Multiplier-less Massive Parallel Processor
Hyunbin Park, Dohyun Kim, Shiho Kim
Computationally intensive Inference tasks of Deep neural networks have enforced revolution of new accelerator architecture to reduce power consumption as well as latency. The key f…
Digital Neuron: A Hardware Inference Accelerator for Convolutional Deep Neural Networks
Hyunbin Park, Dohyun Kim, Shiho Kim
We propose a Digital Neuron, a hardware inference accelerator for convolutional deep neural networks with integer inputs and integer weights for embedded systems. The main idea to…
Safety Requirement Specifications for Connected Vehicles
Madhusudan Singh, Shiho Kim
In the coming years, transportation system will be revamped in a manner that there will be more intelligent and autonomous vehicle phenomenon around us such as smart cars, auto dri…
Intelligent Vehicle-Trust Point: Reward based Intelligent Vehicle Communication using Blockchain
Madhusudan Singh, Shiho Kim
The Intelligent vehicle (IV) is experiencing revolutionary growth in research and industry, but it still suffers from many security vulnerabilities. Traditional security methods ar…