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I am a researcher in Computer Vision and Artificial Intelligence, specializing in facial recognition and person re-identification systems. My research focuses on developing robust algorithms for facial recognition, age transfer modeling, and person re-identification using various deep learning approaches. I've worked on several projects implementing GANs for super-resolution, facial feature extraction, and cross-input neighborhood difference techniques to enhance recognition accuracy across different scenarios. |
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Camera Detection for Information Leakage Prevention - Samsung SDS Video Security Solution
Development of a camera detection model for information leakage prevention. Custom dataset construction. |
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IR Liveness Detection - NIR(Near-Infrared) camera
IR liveness detection model development based on resnet architecture for real/fake face discrimination. Custom dataset planning and collection due to data scarcity. |
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X-ray Multi-object Detection AI Training Dataset Construction (NIA 한국정보화진흥원)
Intelligent Carry-on Baggage Screening System Development (국토교통부) Designed and trained a YOLOv5-based model for multi-object recognition in X-ray imagery Refined datasets by eliminating noise and merging semantically overlapping classes. |
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2022 AI Dataset Development Support Program: Facial Aging Image Dataset (NIA 한국정보화진흥원)
Assessment of dataset suitability for training purposes. - Age estimation model training using C3AE. - Age transformation face generation using SAM. |
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2022 AI Dataset Development Support Program: Multi-Object 2D/3D Representation Dataset (NIA 한국정보화진흥원)
Validation Using YOLOR for Training Dataset Suitability. Chosen for balanced inference speed, accuracy, and representation learning capacity. |
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Utilizing the DECA Model for 3D Face Dataset Generation
Generating 3D face data for use in other internal projects. High-fidelity facial reconstruction with diverse expressions, without the need for actual 3D scanning. |
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Two-stage person re-identification scheme using cross-input neighborhood differences
Hyeonwoo Kim, Hyungjoon Kim, Bumyeon Ko, Jonghwa Shim, Eenjun Hwang The Journal of Supercomputing, 2022 Two-stage person re-identification framework with spatial feature extraction and comparison network. |
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A Cross-age Kinship Verification Scheme Using Face Age Transfer Model
Hyeonwoo Kim, Hyungjoon Kim, Bumyeon Ko, Eenjun Hwang 2022 IEEE International Conference on Big Data and Smart Computing (BigComp), 2022 Face age transfer-based kinship verification for age-invariant representation and improved accuracy. |
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Person Re-identification Scheme Using Cross-Input Neighborhood Differences
Hyeonwoo Kim, Hyungjoon Kim, Bumyeon Ko, Eenjun Hwang The 22nd International Conference on Artificial Intelligence, 2021 Triple-input feature reconstruction model for simultaneous similarity and difference analysis in person re-identification. |
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Review Photo Validation Scheme Based on Faster R-CNN and Triplet Loss
Seongkuk Cho, Hyungjoon Kim, Bumyeon Ko, Eenjun Hwang The 6th International Conference on Next Generation Computing 2020 (ICNGC 2020), 2020 Deep learning-based clothing review verification using Faster R-CNN and triplet loss for fraudulent photo detection. |
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초해상화 GAN 을 활용한 저해상도 얼굴 인식 기법
고범연, 김현우, 조성국, 황인준 한국정보과학회 2021 한국소프트웨어종합학술대회 (KSC), 2021 Low-resolution face recognition using super-resolution GAN for enhanced identity verification performance. |
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얼굴 특징점을 활용한 딥러닝 기반의 유사 얼굴 인식 기법
고범연, 김현우, 조성국, 황인준 Korean DataBase Conference (KDBC), 2021 Facial landmark-based similar face recognition for objective similarity assessment and improved performance. |
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FaceNet 과 얼굴 특징점 추출기를 활용한 정면 얼굴 인식 기법
김현우, 고범연, 심종화, 정원용, 황인준 한국정보과학회 2020 한국소프트웨어종합학술대회 (KSC), 2020 Facial landmark-based similarity integration for interpretable and enhanced face recognition using FaceNet. |
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시맨틱 얼굴 이미지 분할과 Triplet Loss 를 활용한 얼굴 인식 기법
고범연, 김현우, 유제혁, 황인준 한국정보과학회 2020 한국컴퓨터종합학술대회 (KCC), 2020 Semantic segmentation-based face recognition using triplet loss for background-robust identity verification. |
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