no code implementations • 22 Feb 2024 • Junyoung Choi, Sagnik Bhattacharya, Joohyun Lee
DynaPose is based on line-of-sight (LOS) and non-LOS (NLOS) classification using deep learning for anchor selection and pose prediction.
no code implementations • 16 Feb 2024 • Sagnik Bhattacharya, Junyoung Choi, Joohyun Lee
In this paper, we propose and implement a novel low-power channel-aware dynamic frequency DL-TDOA ranging algorithm.
no code implementations • 13 Feb 2024 • Junyoung Choi, Sagnik Bhattacharya
As commercial interest in proximity services increased, the development of various wireless localization techniques was promoted.
1 code implementation • 4 Dec 2023 • Sunjae Lee, Junyoung Choi, Jungjae Lee, Munim Hasan Wasi, Hojun Choi, Steven Y. Ko, Sangeun Oh, Insik Shin
The advent of large language models (LLMs) has opened up new opportunities in the field of mobile task automation.
no code implementations • 3 Sep 2021 • Junyoung Choi, Hakjun Lee, Suyeon Kim, Seok-Kyu Kwon, Won-Ki Jeong
It is known that the morphology of mitochondria is closely related to the functions of neurons and neurodegenerative diseases.
no code implementations • EACL 2021 • Ohjoon Kwon, Dohyun Kim, Soo-Ryeon Lee, Junyoung Choi, SangKeun Lee
Word embedding is considered an essential factor in improving the performance of various Natural Language Processing (NLP) models.
no code implementations • 15 Apr 2019 • Minsung Hyun, Junyoung Choi, Nojun Kwak
In reinforcement learning (RL), temporal abstraction still remains as an important and unsolved problem.
no code implementations • 13 Mar 2019 • Junyoung Choi, Minsung Hyun, Nojun Kwak
We propose a new low-cost machine-learning-based methodology which assists designers in reducing the gap between the problem and the solution in the design process.
no code implementations • 27 Nov 2017 • YoungJoon Yoo, SeongUk Park, Junyoung Choi, Sangdoo Yun, Nojun Kwak
In addition to this performance enhancement problem, we show that the proposed PGN can be adopted to solve the classical adversarial problem without utilizing the information on the target classifier.