Publications

See also my full profile on Google Scholar.

2026

1. TIU-ReID: Target Identity Unlearning for Person Re-Identification

   J. Chen, Dongyoun Kim, Chulwoo Pack, and 2 more authors

   In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2026
2. Integrating Artificial Intelligence with Wearable Sensors for Advanced Health Monitoring and Diagnosis

   Dongyoun Kim, S. S. Ahmed, A. Amjad, and 2 more authors

   Biosensors, 2026

2025

1. Structure- and Semantic-based Rationale Distillation: Table and Chart Question Answering in Scientific Documents

   Dongyoun Kim, W. Heo, J. H. Lee, and 1 more author

   In Proceedings of the International Conference on Research in Adaptive and Convergent Systems (RACS), 2025

2024

1. Comparative Analysis of Deep Learning-based Anomaly Detection Models for GPS Spoofing Detection

   H. Mirzakhaninafchi, Chulwoo Pack, Dongyoun Kim, and 2 more authors

   In Proceedings of the International Conference on Research in Adaptive and Convergent Systems (RACS), 2024
2. Extracting Information from Scientific Literature via Visual Table Question Answering Models

   Dongyoun Kim, H. Choi, Y. Jang, and 1 more author

   In Proceedings of the International Conference on Research in Adaptive and Convergent Systems (RACS), 2024
3. A Novel Dataset for Flood Detection Robust to Seasonal Changes in Satellite Imagery

   Y. Jang, Dongyoun Kim, Chulwoo Pack, and 1 more author

   In Proceedings of the International Conference on Research in Adaptive and Convergent Systems (RACS), 2024

2023

1. Weakly-supervised Semantic Segmentation on Historical Document Images

   Chulwoo Pack, and Dongyoun Kim

   In Proceedings of the 2023 International Conference on Research in Adaptive and Convergent Systems, 2023

   Abs

   Weakly-Supervised Semantic Segmentation (WSSS) has been widely studied as a feasible option to reduce the expensive annotation costs of deep semantic segmentation models. While numerous studies have proposed novel approaches for generating pseudo-labels and demonstrated their effectiveness, their domain is limited to natural scene images. There is a growing need for a comprehensive exploration of WSSS in the domain of document images, given the increasing number of digitized historical document images and the growing importance of document image segmentation for successful information retrieval. Importantly, document images possess inherent characteristics that distinguish them from natural scene images, rendering conventional image-level labels unsuitable. Consequently, the application of recent WSSS frameworks designed for natural scene images is limited. In this work, we propose a simple yet effective pseudo-label generation technique using content-adaptive geometric feature analysis. This approach enables the training of a segmentation model in a weakly-supervised manner without relying on image-level labels. Our method utilizes a Gravity-map, which can highlight potential regions of interest without requiring a priori-knowledge, serving as an initial coarse pixel-level label. The Gravity-map is subsequently refined through simple binarization and noise removal to form a pseudo-label. Finally, a segmentation model is trained using the generated pseudo-labels. Experimental results on the publicly available historical document collection demonstrate that the proposed pseudo-label generation technique offers a viable option for training the semantic segmentation model in the document image domain.

2. Compressive strength prediction of ternary-blended concrete using deep neural network with tuned hyperparameters

   Ju-Hee Choi, Dongyoun Kim, Min-Sam Ko, and 3 more authors

   Journal of Building Engineering, 2023

2021

1. Efficient Object Detection Model for Real-time UAV Application

   Subrahmanyam Vaddi, Dongyoun Kim, Chandan Kumar, and 2 more authors

   Computer and Information Science, 2021

2019

1. Development of a semantic scene conversion model for image-based localization at night

   Dongyoun Kim, Sangwon Shin, Jinwoo Park, and 1 more author

   In Proceedings of the Conference on Research in Adaptive and Convergent Systems, 2019

2018

1. Development of automated 3D knee bone segmentation with inhomogeneity correction for deformable approach in magnetic resonance imaging

   Dongyoun Kim, Jiyoung Lee, Joon Shik Yoon, and 2 more authors

   In Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems, 2018
2. Texture weighted fuzzy C-means algorithm for 3D brain MRI segmentation

   Ji Young Lee, Dongyoun Kim, Jin Yeong Mun, and 3 more authors

   In Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems, 2018

2017

1. Extract texture-problematic femur from Knee MRI using Fuzzy C-means and Region Growing approach

   JY Mun, JY Lee, DY Kim, and 1 more author

   In International Conference on Internet, 2017
2. Identification of the White-Mold affected Soybean fields by using Multispectral Imageries, Spatial Autocorrelation and Support Vector Machine

   Sae-han Suh, Dong-youn Kim, Ji-eun Jhang, and 3 more authors

   In Proceedings of the International Conference on Research in Adaptive and Convergent Systems, 2017