8 citations · 17 across the 8 of their papers we have counts for
6 papers · 1 filter
Spatially-weighted Anomaly Detection
Minori Narita, Daiki Kimura, Ryuki Tachibana
Many types of anomaly detection methods have been proposed recently, and applied to a wide variety of fields including medical screening and production quality checking. Some metho…
Injective State-Image Mapping facilitates Visual Adversarial Imitation Learning
Subhajit Chaudhury, Daiki Kimura, Asim Munawar +1
The growing use of virtual autonomous agents in applications like games and entertainment demands better control policies for natural-looking movements and actions. Unlike the conv…
Focusing on What is Relevant: Time-Series Learning and Understanding using Attention
Phongtharin Vinayavekhin, Subhajit Chaudhury, Asim Munawar +4
This paper is a contribution towards interpretability of the deep learning models in different applications of time-series. We propose a temporal attention layer that is capable of…
MaestROB: A Robotics Framework for Integrated Orchestration of Low-Level Control and High-Level Reasoning
Asim Munawar, Giovanni De Magistris, Tu-Hoa Pham +5
This paper describes a framework called MaestROB. It is designed to make the robots perform complex tasks with high precision by simple high-level instructions given by natural lan…
DAQN: Deep Auto-encoder and Q-Network
Daiki Kimura
The deep reinforcement learning method usually requires a large number of training images and executing actions to obtain sufficient results. When it is extended a real-task in the…
Internal Model from Observations for Reward Shaping
Daiki Kimura, Subhajit Chaudhury, Ryuki Tachibana +1
Reinforcement learning methods require careful design involving a reward function to obtain the desired action policy for a given task. In the absence of hand-crafted reward functi…