Search

Your search keyword '"Shin, Heejung"' showing total 10 results
Start Over Author "Shin, Heejung"
10 results on '"Shin, Heejung"'

1. Enhancing Exploration Efficiency using Uncertainty-Aware Information Prediction

Author

Kim, Seunghwan, Shin, Heejung, Yim, Gaeun, Kim, Changseung, and Oh, Hyondong

Subjects
Computer Science - Robotics
Abstract

Autonomous exploration is a crucial aspect of robotics, enabling robots to explore unknown environments and generate maps without prior knowledge. This paper proposes a method to enhance exploration efficiency by integrating neural network-based occupancy grid map prediction with uncertainty-aware Bayesian neural network. Uncertainty from neural network-based occupancy grid map prediction is probabilistically integrated into mutual information for exploration. To demonstrate the effectiveness of the proposed method, we conducted comparative simulations within a frontier exploration framework in a realistic simulator environment against various information metrics. The proposed method showed superior performance in terms of exploration efficiency., Comment: 7pages

Published
2024

7. "ImagiNATION is my nation."

Author

Shin, Heejung

Subjects
Fine arts, Performing arts, Feminism, Language, Migration, Women of color
Abstract

"Imagination is my nation, and that is where I want to live and die."- Guillermo Gómez-PeñaIntroIn this paper, I discuss artistic subjects and themes that were featured in my project, 호올 (Whore/Hole/Whole) (2017), and more recent work, Free Fish”es” (2018), that stemmed from my three-years residence practice at the Visual Arts Department, the University of California, San Diego. A Korean transcription of multiple English terms whose sounds are clearly distinguishable to English speakers but suggest little distinctions to Korean speakers, 호올 (Whore/Hole/Whole) is an attempt to defy the hierarchy of languages and gender inequality by adopting forms of rap music video, dance and vernacular swear words. In the exhibition, viewers are embedded in the counter-representational space against patriarchal, white-supremacist, hetero-normative institutions of language, gender, and race that marginalize women of color and hyphenated Americans. Free Fish”es” imagines the world of immigration and border policing as the vast body of water in which the migrant body as fish has to navigate and confront obstacles, which endlessly confines migrants into the water. Why the sea and the sky both have the same color—BLUE—but are not traversable? Let’s make fish fly. Let’s break the horizon, the borderline.

Published
2018

10. Deep Learning-Based Human Detection Using RGB and IR Images from Drones

Author

Bae, Seonguk, Shin, Heejung, Kim, Hyeongseop, Park, Minkyu, Choi, Myong-Yol, and Oh, Hyondong

Abstract

This paper proposes an object detection algorithm based on a deep neural network which utilizes RGB and infrared (IR) images for human detection with drones. Although there are some public RGB image datasets in aerial view, there is no publicly available dataset in which both RGB and IR images are taken simultaneously with drones. Thus, we collect RGB and IR images at various altitudes on our own. However, the detection performance of the RGB and IR-based algorithm is limited, because there are more available RGB images for training than IR images or RGB and IR images taken simultaneously. To address this data imbalance, we use a generative adversarial neural network model called CycleGAN to generate IR images from RGB images in the public and self-collected dataset. Furthermore, the neural network for object detection is accelerated by neural network quantization and optimization to execute the algorithm faster on an embedded computing board. To shorten the search time and improve the robustness of detection, we employ a formation flight of multiple drones for human detection. The effectiveness of the integrated system of formation flight and onboard human detection algorithm is validated by the real flight experiment to find humans who are in a wide and wild area.

Published
2023
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results