Zobrazeno 1 - 10
of 247
pro vyhledávání: '"Jong-Ok Kim"'
Publikováno v:
IEEE Access, Vol 12, Pp 111360-111370 (2024)
Low-light images often lack visibility and information, and traditional methods of adjusting camera sensitivity and exposure time can result in visual quality degradation. In this paper, we propose a low-light enhancement method that utilizes two nov
Externí odkaz:
https://doaj.org/article/57acae8510514c5d914696aacd2b985a
Publikováno v:
IEEE Access, Vol 12, Pp 105651-105661 (2024)
This paper proposes to utilize deep spatio-spectral features for color constancy, while most conventional methods focus on only spatial information of RGB images. We propose a novel color constancy method that exploits multi-band near-infrared (NIR).
Externí odkaz:
https://doaj.org/article/7bded4fba44f4fa5937dc72514e9d441
Autor:
Goo-Young Moon, Jong-Ok Kim
Publikováno v:
IEEE Access, Vol 12, Pp 63725-63734 (2024)
We aim to contribute to deep learning based smart agriculture through semantic segmentation on crop images from real field environment. The key objective is the precise detection of diseases to facilitate the automation of agricultural management. Th
Externí odkaz:
https://doaj.org/article/d43de0bd13e44e33bff5230f502fc487
Publikováno v:
Plant Methods, Vol 19, Iss 1, Pp 1-11 (2023)
Abstract Background Light control technology has been developed and studied for decades in controlled environment agriculture (CEA) for successful crop production. The effects of the light spectrum on plant growth can vary because plants have spectra
Externí odkaz:
https://doaj.org/article/57d2ff503cb94d2391859992b83fd977
Publikováno v:
IEEE Access, Vol 11, Pp 41770-41782 (2023)
This paper proposes an image formation model that jointly combines dichromatic and intrinsic image decomposition models. The two decomposition models analyze image formation process from a different perspective, and they can be combined synergistical
Externí odkaz:
https://doaj.org/article/cced5690761f4246ba944c0eddcc5e7f
Publikováno v:
IEEE Access, Vol 11, Pp 20136-20149 (2023)
This paper proposes a deep highlight removal method based on the dichromatic model under alternating current (AC) light sources with a new diffuse prior on temporal domain, temporal dark prior. An input image is decomposed into specular and diffuse c
Externí odkaz:
https://doaj.org/article/1513d68b0c6c424095fa6f4ca5d0a4c8
Publikováno v:
IEEE Access, Vol 10, Pp 122286-122301 (2022)
Image denoising is a highly challenging problem yet important task in image processing. Recently, many CNN-based denoising methods have made great performances but they commonly denoise blindly texture and non-texture regions together. This frequentl
Externí odkaz:
https://doaj.org/article/47e12659504942209575bcf29ddc8f8a
A Novel Shape Based Plant Growth Prediction Algorithm Using Deep Learning and Spatial Transformation
Publikováno v:
IEEE Access, Vol 10, Pp 37731-37742 (2022)
Plant growth prediction is challenging, as the growth rate varies depending on environmental factors. It is an essential task for efficient cultivation in controlled environments, such as in plant factories. In this paper, we propose a novel deep lea
Externí odkaz:
https://doaj.org/article/02518f8675a64fb5b89b81fa8b04a3dd
Publikováno v:
IEEE Access, Vol 10, Pp 4763-4776 (2022)
Plants exhibit dynamic changes as they grow. For example, a new leaf may appear suddenly, and rotate and fold over time. Therefore, it is difficult to predict the growth of plants. For accurate growth predictions, it is important to predict the shape
Externí odkaz:
https://doaj.org/article/cdea6751cbcc4e55aa263036270a96e9
Publikováno v:
IEEE Access, Vol 10, Pp 15528-15538 (2022)
Artificial lights, which are powered by alternating current (AC), are ubiquitous nowadays. The intensity of these lights fluctuates dynamically depending on the AC power. In contrast to previous color constancy methods that exploited the spatial colo
Externí odkaz:
https://doaj.org/article/8be90e1580484a13a2bc699bf066fcdd