Seon Ho Kim

ORCID: 0000-0002-8410-0839
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About
Contact & Profiles
Research Areas
  • Video Surveillance and Tracking Methods
  • Geographic Information Systems Studies
  • Infrastructure Maintenance and Monitoring
  • Muscle Physiology and Disorders
  • Traffic Prediction and Management Techniques
  • Anomaly Detection Techniques and Applications
  • Automated Road and Building Extraction
  • Data Management and Algorithms
  • Textile materials and evaluations
  • Image Retrieval and Classification Techniques
  • Geophysical Methods and Applications

University of Southern California
2015-2024

Southern California University for Professional Studies
2018

Monitoring public facilities is essential for governments to establish safer, cleaner, and more resilient cities, ultimately benefiting all citizens. One promising approach facility surveillance employ visual machine-learning methods on street scenes. The potential development advancements in such state-of-the-art require the availability of datasets annotated with several defects (e.g., illegal dumping, graffiti, potholes, damaged traffic signs). Towards this, we introduce "StreetLens", a...

10.1145/3625468.3652188 article EN mit 2024-04-15

The measurement of wisdom has used self report questionnaires and performance measures (e.g., the Berlin Wisdom Paradigm).We aimed to bridge two by creating a questionnaire measure using vignettes offering three response options at different levels wisdom.While Cronbach's α was poor based on total sample (n = 167), cluster analysis identified groupings with similar patterns scale.The group highest mean score included one third sample, middle aged (M 44.7),and level education college...

10.1093/geront/gnv552.04 article EN The Gerontologist 2015-10-23

The measurement of wisdom has used self report questionnaires and performance measures (e.g., the Berlin Wisdom Paradigm).We aimed to bridge two by creating a questionnaire measure using vignettes offering three response options at different levels wisdom.While Cronbach's α was poor based on total sample (n = 167), cluster analysis identified groupings with similar patterns scale.The group highest mean score included one third sample, middle aged (M 44.7),and level education college...

10.1093/geront/gnv552.05 article EN The Gerontologist 2015-10-23
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