Zobrazeno 1 - 10 of 27 pro vyhledávání: '"Yeong-Jun Cho"'
1
Akademický článek
Human Motion Prediction by Combining Spatial and Temporal Information With Independent Global Orientation
Autor: Hanwool Kim, Choonsung Shin, Yeong-Jun Cho
Publikováno v: IEEE Access, Vol 11, Pp 98818-98829 (2023)
In this study, we address the challenge of 3D human motion prediction from motion capture data, which has become critical in various applications such as autonomous vehicles and human-robot interaction. Previous deep learning-based methods have impro
Externí odkaz: https://doaj.org/article/955c65e316314cc8985fcced6a23d804
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2
Akademický článek
Rethinking Multi-Object Tracking Based on Re-Identification and Appearance Model Management
Autor: Yeong-Jun Cho, Dohyung Kim
Publikováno v: IEEE Access, Vol 11, Pp 54337-54351 (2023)
Conventional multi-object tracking (MOT) methods often fail to track objects that repeatedly disappear and reappear in the scene due to occlusion or moving off the screen. Previous studies have used motion and appearance information to address these
Externí odkaz: https://doaj.org/article/3e47cd70615b4fe68267ab9a48de2fcf
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3
Akademický článek
Analysis of Training Deep Learning Models for PCB Defect Detection
Autor: Joon-Hyung Park, Yeong-Seok Kim, Hwi Seo, Yeong-Jun Cho
Publikováno v: Sensors, Vol 23, Iss 5, p 2766 (2023)
Recently, many companies have introduced automated defect detection methods for defect-free PCB manufacturing. In particular, deep learning-based image understanding methods are very widely used. In this study, we present an analysis of training deep
Externí odkaz: https://doaj.org/article/354ba23837dc46cbbda027cc02e5e0fd
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4
Akademický článek
Product Inspection Methodology via Deep Learning: An Overview
Autor: Tae-Hyun Kim, Hye-Rin Kim, Yeong-Jun Cho
Publikováno v: Sensors, Vol 21, Iss 15, p 5039 (2021)
In this study, we present a framework for product quality inspection based on deep learning techniques. First, we categorize several deep learning models that can be applied to product inspection systems. In addition, we explain the steps for buildin
Externí odkaz: https://doaj.org/article/3bb62421f66a45a7aca044a7651a751a
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9
Distance-based camera network topology inference for person re-identification
Autor: Kuk-Jin Yoon, Yeong-Jun Cho
Publikováno v: Pattern Recognition Letters. 125:220-227
In this paper, we propose a novel distance-based camera network topology inference method for efficient person re-identification. To this end, we first calibrate each camera and estimate relative scales between cameras. Using the calibration results
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ce14c74f2857cefedb81c7cdd46304c5
https://doi.org/10.1016/j.patrec.2019.04.009
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