Hyunmin Lee

ORCID: 0000-0003-4191-5357
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About
Contact & Profiles
Research Areas
  • Explainable Artificial Intelligence (XAI)
  • Advanced Malware Detection Techniques
  • Anomaly Detection Techniques and Applications
  • Scientific Computing and Data Management
  • Ethics and Social Impacts of AI
  • Digital Accessibility for Disabilities
  • Multimodal Machine Learning Applications
  • Tactile and Sensory Interactions
  • Hate Speech and Cyberbullying Detection
  • Spam and Phishing Detection
  • Data Visualization and Analytics

University of Seoul
2023-2024

Alternative (alt) text is essential for people with visual impairments to acquire information about image content through a screen reader. However, collecting images and creating alt requires time effort. To deal this problem, automatically that have no ensure all in web page has their text. Additionally, automatic limitations accuracy quality compared human-created despite the improvements recognition natural language process technology. We present WATAA, authoring assistant collects...

10.1145/3581754.3584127 article EN 2023-03-26

Artificial intelligence (AI) gives many benefits to our lives. However, biased AI models created by receiving data poisoning attacks may induce social problems. Therefore, developers must consider carefully whether the training received a poison attack when developing an model. Data visualization is one of methods facilitate analysis required for checking if attack. prior studies did not visualize real-world data. Restaurant reviews in delivery apps are cases poisoned dataset. Restaurants...

10.1145/3581754.3584128 article EN 2023-03-26

The increasing performance of machine learning (ML) models necessitates greater computing resources, contributing to rising carbon intensity in ML and raising concerns about computational equity. Previous studies focused on developing tools that enable model developers view the training process. Still, little is known how support online communities explore during inference. We developed MIEV, a inference emission visualizer, supports TensorFlow Hub image domain Inference phase. also provide...

10.1145/3584931.3606959 article EN 2023-10-13

In online food delivery apps, customers write reviews to reflect their experiences. However, certain restaurants use a "review event" strategy solicit favorable from and boost revenue. Review event is marketing where restaurant owner gives free services in return for promise review. Nevertheless, current datasets of app neglect this situation. Furthermore, there appears be an absence with written Korean. To solve gap, paper presents dataset that contains obtained on Korean which review...

10.1016/j.dib.2024.110598 article EN cc-by-nc Data in Brief 2024-06-05
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