Zobrazeno 1 - 10 of 81 pro vyhledávání: '"Kwang-Eun Ko"'
4
Multi-tasking deep convolutional network architecture design for extracting nonverbal communicative information from a face
Autor: Heereen Shim, Kwang-Eun Ko, Inhoon Jang, Kwee-Bo Sim, Kyunghwan Cho
Publikováno v: Cognitive Systems Research. 52:658-667
Facial expressions convey not only emotions but also communicative information. Therefore, facial expressions should be analysed to understand communication. The objective of this study is to develop an automatic facial expression analysis system for
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::b902ebdb8a71833ff91a1eb62f3c090d
https://doi.org/10.1016/j.cogsys.2018.08.006
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5
Stochastic Decision Fusion of Convolutional Neural Networks for Tomato Ripeness Detection in Agricultural Sorting Systems
Autor: Jeong Ho Lim, Kwang-Eun Ko, Inhoon Jang, Da Uhm Lee, Jeong Hee Choi
Publikováno v: Sensors, Vol 21, Iss 917, p 917 (2021)
Sensors
Volume 21
Issue 3
Sensors (Basel, Switzerland)
Advances in machine learning and artificial intelligence have led to many promising solutions for challenging issues in agriculture. One of the remaining challenges is to develop practical applications, such as an automatic sorting system for after-r
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::80957dc81d9e6d1329944f8c738b9531
https://www.mdpi.com/1424-8220/21/3/917
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7
Development of Behavior Understanding System based on Object-Human Interaction Pattern Extraction using Deep Learning Model
Autor: Kwee-Bo Sim, Kwang-Eun Ko, Heereen Shim
Publikováno v: Journal of Institute of Control, Robotics and Systems. 24:57-63
Human-Robot Interaction (HRI) technology plays a key role in social robotics. The main goal of HRI studies is to develop robots that can communicate with humans through an intuitive interface. In this paper, we focused on the Human Action Understandi
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::74496a1f5749a55b00cfa76e1e422cda
https://doi.org/10.5302/j.icros.2018.17.0119
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8
Deep convolutional framework for abnormal behavior detection in a smart surveillance system
Autor: Kwee-Bo Sim, Kwang-Eun Ko
Publikováno v: Engineering Applications of Artificial Intelligence. 67:226-234
The ability to instantly detect risky behavior in video surveillance systems is a critical issue in a smart surveillance system. In this paper, a unified framework based on a deep convolutional framework is proposed to detect abnormal human behavior
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::f033f0bfe7da260f4768e37470f2547c
https://doi.org/10.1016/j.engappai.2017.10.001
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