Zobrazeno 1 - 10
of 126
pro vyhledávání: '"Jongweon Kim"'
Autor:
Youngseok Lee, Jongweon Kim
Publikováno v:
Applied Sciences, Vol 13, Iss 17, p 9722 (2023)
In the past few years, deep convolutional neural networks (DCNNs) have surpassed human performance in tasks related to recognizing objects. However, DCNNs are also threatened by performance degradation due to adversarial examples. DCNNs are essential
Externí odkaz:
https://doaj.org/article/398f6e7371934b349d68160d99c9a30a
Autor:
Youngseok Lee, Jongweon Kim
Publikováno v:
Applied Sciences, Vol 13, Iss 7, p 4422 (2023)
In recent years, artificial intelligence technologies in vision tasks have gradually begun to be applied to the physical world, proving they are vulnerable to adversarial attacks. Thus, the importance of improving robustness against adversarial attac
Externí odkaz:
https://doaj.org/article/130593da05cb421ba9664fa38eb917b3
Autor:
DaYou Jiang, Jongweon Kim
Publikováno v:
Applied Sciences, Vol 11, Iss 12, p 5701 (2021)
This paper presents a new content-based image retrieval (CBIR) method based on image feature fusion. The deep features are extracted from object-centric and place-centric deep networks. The discrete cosine transform (DCT) solves the strong correlatio
Externí odkaz:
https://doaj.org/article/2b4a1a52cf844f9cb18464fac93c5313
Autor:
Yiyu Hong, Jongweon Kim
Publikováno v:
Applied Sciences, Vol 9, Iss 14, p 2780 (2019)
High Efficiency Advanced Audio Coding (HE-AAC) is a lossy compression method for digital audio data which supplies high-quality audio at a very low bit rate. In this paper, the audio blind watermarking algorithm, on the basis of autocorrelation modul
Externí odkaz:
https://doaj.org/article/0cfa8ba120154212ad913a407968c5ba
Autor:
DaYou Jiang, Jongweon Kim
Publikováno v:
Applied Sciences, Vol 8, Iss 10, p 1735 (2018)
This work presents a novel shot boundary detection (SBD) method based on the Place-centric deep network (PlaceNet), with the aim of using video shots and image queries for video searching (VS) and fingerprint detection. The SBD method has three stage
Externí odkaz:
https://doaj.org/article/206464f3a84b4d83b004bbca76844661
Autor:
Yiyu Hong, Jongweon Kim
Publikováno v:
Applied Sciences, Vol 7, Iss 10, p 988 (2017)
With the rapid development of three-dimensional (3D) technology and an increase in the number of available models, issues with copyright protection of 3D models are inevitable. In this paper, we propose a 2D-view depth image- and convolutional neural
Externí odkaz:
https://doaj.org/article/782cba1364eb48e0bebf8d56fdbd38ae
Autor:
Xun Jin, Jongweon Kim
Publikováno v:
Applied Sciences, Vol 7, Iss 8, p 764 (2017)
In this paper, we propose a 3 dimensional (3D) model identification method based on weighted implicit shape representation (WISR) and panoramic view. The WISR is used for 3D shape normalization. The 3D shape normalization method normalizes a 3D model
Externí odkaz:
https://doaj.org/article/ce86718ea68f42c0bd2377737c0b4acf
Autor:
Xun Jin, Jongweon Kim
Publikováno v:
Applied Sciences, Vol 7, Iss 5, p 528 (2017)
With the increased development of 360-degree production technologies, artwork has recently been photographed without authorization. To prevent this infringement, we propose an artwork identification methodology for 360-degree images. We transform the
Externí odkaz:
https://doaj.org/article/bbaa1a8807904b428ece7787b437ea08
Autor:
Xun Jin, Jongweon Kim
Publikováno v:
Applied Sciences, Vol 7, Iss 2, p 139 (2017)
A three-dimensional (3D) skeletonization algorithm extracts the skeleton of a 3D model and provides it for many applications, such as 3D model classification and identification. There are three major skeletonization methodologies used in the literatu
Externí odkaz:
https://doaj.org/article/aa27d0b7764e40d5baaf138e58f2aa51
Autor:
De Li, JongWeon Kim
Publikováno v:
International Journal of Distributed Sensor Networks, Vol 10 (2014)
We created a robust and secure forensic marking algorithm through the process of hiding information in a two-dimensional (2D) barcode and embedding it into the discrete wavelet transformation-discrete fractional random transformation (DWT-DFRNT) doma
Externí odkaz:
https://doaj.org/article/d6d370e7c8734e64ad6a3d07703a47de