Výsledky vyhledávání

Akademický článek

INSANet: INtra-INter Spectral Attention Network for Effective Feature Fusion of Multispectral Pedestrian Detection

Autor: Sangin Lee, Taejoo Kim, Jeongmin Shin, Namil Kim, Yukyung Choi

Publikováno v: Sensors, Vol 24, Iss 4, p 1168 (2024)

Pedestrian detection is a critical task for safety-critical systems, but detecting pedestrians is challenging in low-light and adverse weather conditions. Thermal images can be used to improve robustness by providing complementary information to RGB

Externí odkaz: https://doaj.org/article/a007b7c6c73048daaf5822544209444c

Zobrazit plný text záznamu

Plný text ve formátu HTML

Akademický článek

Neutron imaging for metallurgical characteristics of iron products manufactured with ancient Korean iron making techniques

Autor: Sungmo Cho, Jongyul Kim, TaeJoo Kim, Hirotaka Sato, Ilkwon Huh, Namchul Cho

Publikováno v: Nuclear Engineering and Technology, Vol 53, Iss 5, Pp 1619-1625 (2021)

This paper demonstrates the possible nondestructive analysis of iron artifacts’ metallurgical characteristics using neutron imaging. Ancient kingdoms of the Korean Peninsula used a direct smelting process for ore smelting and iron bloom production;

Externí odkaz: https://doaj.org/article/7c1e50e11827480da4bada0fb0a561cd

Zobrazit plný text záznamu

Akademický článek

Multispectral Benchmark Dataset and Baseline for Forklift Collision Avoidance

Autor: Hyeongjun Kim, Taejoo Kim, Won Jo, Jiwon Kim, Jeongmin Shin, Daechan Han, Yujin Hwang, Yukyung Choi

Publikováno v: Sensors, Vol 22, Iss 20, p 7953 (2022)

In this paper, multispectral pedestrian detection is mainly discussed, which can contribute to assigning human-aware properties to automated forklifts to prevent accidents, such as collisions, at an early stage. Since there was no multispectral pedes

Externí odkaz: https://doaj.org/article/30b4a265ce0b4b04beee5816e212e158

Zobrazit plný text záznamu

Plný text ve formátu HTML

Akademický článek

Instance-Aware Plant Disease Detection by Utilizing Saliency Map and Self-Supervised Pre-Training

Autor: Taejoo Kim, Hyeongjun Kim, Kyeonghoon Baik, Yukyung Choi

Publikováno v: Agriculture, Vol 12, Iss 8, p 1084 (2022)

Plant disease detection is essential for optimizing agricultural productivity and crop quality. With the recent advent of deep learning and large-scale plant disease datasets, many studies have shown high performance of supervised learning-based plan

Externí odkaz: https://doaj.org/article/0c61cae157084c70ba1cc0d3d43fe6c8

Zobrazit plný text záznamu

Akademický článek

Crop Growth Monitoring System in Vertical Farms Based on Region-of-Interest Prediction

Autor: Yujin Hwang, Seunghyeon Lee, Taejoo Kim, Kyeonghoon Baik, Yukyung Choi

Publikováno v: Agriculture, Vol 12, Iss 5, p 656 (2022)

Vertical farms are to be considered the future of agriculture given that they not only use space and resources efficiently but can also consistently produce large yields. Recently, artificial intelligence has been introduced for use in vertical farms

Externí odkaz: https://doaj.org/article/c16c7e5811f143b4a96490f516a1dbd0

Zobrazit plný text záznamu

Akademický článek

Interactive ion-mediated sap flow regulation in olive and laurel stems: physicochemical characteristics of water transport via the pit structure.

Autor: Jeongeun Ryu, Sungsook Ahn, Seung-Gon Kim, TaeJoo Kim, Sang Joon Lee

Publikováno v: PLoS ONE, Vol 9, Iss 5, p e98484 (2014)

Sap water is distributed and utilized through xylem conduits, which are vascular networks of inert pipes important for plant survival. Interestingly, plants can actively regulate water transport using ion-mediated responses and adapt to environmental

Externí odkaz: https://doaj.org/article/d1efa9097b7b43968781a09018df516e

Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání