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Found 21 papers, 1 papers with code
PoseViNet: Distracted Driver Action Recognition Framework Using Multi-View Pose Estimation and Vision Transformer
The proposed method is a vision transformer-based framework with pose estimation and action inference, namely PoseViNet.
Virtual Action Actor-Critic Framework for Exploration (Student Abstract)
In this paper, a novel actor-critic framework namely virtual action actor-critic (VAAC), is proposed to address the challenge of efficient exploration in RL.
Enhanced Transformer Architecture for Natural Language Processing
Transformer is a state-of-the-art model in the field of natural language processing (NLP).
Sensor Fusion by Spatial Encoding for Autonomous Driving
Sensor fusion is critical to perception systems for task domains such as autonomous driving and robotics.
Road Redesign Technique Achieving Enhanced Road Safety by Inpainting with a Diffusion Model
Image inpainting is based on inpainting safe roadway elements in a roadway image, replacing accident-prone (AP) features by using a diffusion model.
Off-Policy Reinforcement Learning with Loss Function Weighted by Temporal Difference Error
We propose a novel method that introduces a weighting factor for each experience when calculating the loss function at the learning stage.
Reinforcement Learning for Predicting Traffic Accidents
As the demand for autonomous driving increases, it is paramount to ensure safety.
Kick-motion Training with DQN in AI Soccer Environment
In this paper, we attempt to use the relative coordinate system (RCS) as the state for training kick-motion of robot agent, instead of using the absolute coordinate system (ACS).
A Lightweight Domain Adaptive Absolute Pose Regressor Using Barlow Twins Objective
In this paper, a domain adaptive training framework for absolute pose regression is introduced.
Power Management in Smart Residential Building with Deep Learning Model for Occupancy Detection by Usage Pattern of Electric Appliances
The proposed algorithm achieves occupancy detection using technical information of electric appliances by 95. 7~98. 4%.
Reinforcement Learning-Based Cooperative P2P Power Trading between DC Nanogrid Clusters with Wind and PV Energy Resources
Power management of nanogrid clusters with P2P power trading is simulated on a distribution test feeder in real time, and the proposed GCN-Bi-LSTM-PPO technique achieving the lowest electricity cost among the RL algorithms used for comparison reduces the electricity cost by 36. 7%, averaging over nanogrid clusters.
Cluster-based Sampling in Hindsight Experience Replay for Robotic Tasks (Student Abstract)
The proposed sampling strategy groups episodes with different achieved goals by using a cluster model and samples experiences in the manner of HER to create the training batch.
Path Planning of Cleaning Robot with Reinforcement Learning
To solve this electricity consumption issue, the problem of efficient path planning for cleaning robot has become important and many studies have been conducted.
Anomaly Detection of Smart Metering System for Power Management with Battery Storage System/Electric Vehicle
A novel smart metering technique capable of anomaly detection was proposed for real-time home power management system.
Development of Charging, Discharging Scheduling Algorithm for Economical and Energy Efficient Operation of Multi EV Charging Station
For the charging station to take a microgrid (MG) structure, an economical and energy-efficient power management scheme is required for the power provision of EVs while considering the local load demand of the MG. For these purposes, this study presents the power management scheme of interdependent MG and EV fleets aided by a novel EV charg-ing/discharging scheduling algorithm.
RelMobNet: End-to-end relative camera pose estimation using a robust two-stage training
For proving texture invariance, we investigate the generalization of the proposed method augmenting the datasets to different scene styles, as ablation studies, using generative adversarial networks.
Sensing accident-prone features in urban scenes for proactive driving and accident prevention
To avoid accidents due to missing these visual cues, this paper proposes a visual notification of AP-features to drivers based on real-time images obtained via dashcam.
Optimal Scheduling of Energy Storage for Power System with Capability of Sensing Short-term Future PV Power Production
A machine learning (ML) model is introduced for scheduling, and predicting variations of the PV power production and load demand.
Smart Metering System Capable of Anomaly Detection by Bi-directional LSTM Autoencoder
Anomaly detection is concerned with a wide range of applications such as fault detection, system monitoring, and event detection.
Power Management of Microgrid Integrated with Electric Vehicles in Residential Parking Station
Lately, increasing number of electric vehicles (EVs) in residential parking station has become an important issue, because excessive number of EVs can destabilize the power system during peak hours with high charging power requested.
Two-stage training algorithm for AI robot soccer
Because these two training processes are conducted in a series in every timestep, agents can learn how to maximize role rewards and team rewards simultaneously.
Multi-agent Reinforcement Learning
reinforcement-learning
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