• Journal of Internet Computing and Services
    ISSN 2287 - 1136 (Online) / ISSN 1598 - 0170 (Print)
    https://jics.or.kr/

Digital Library


Search: "[ keyword: Detect ]" (118)
  1. 91. Development of a Real-Time Dense Fog Detection Framework for Autonomous Drones
  2. 92. Malware Image Classification with Dilated Convolution and Channel Attention in ConvNeXt-Tiny
  3. 93. Dual-Branch Consistency-Based Android Malware Detection
  4. 94. Experimental Quantitative Analysis of Weapon-Related Risk Behaviors in CCTV Using Active Big Data
    Tsagaantsooj Batzaya, Eunbi Cho, Jeong-Hyeon Chang, Kwanghoon Pio Kim, Vol. 26, No. 6, pp. 83-92, Dec. 2025
    10.7472/jksii.2025.26.6.83
    Keywords: CCTV, Risk Behavior, Object Detection, Dynamic interaction, Weapon Analysis
  5. 95. Development of a Fall Detection Monitoring System for the Elderly using YOLOv8
    Doung Uk Kim, Shinhoo Kang, Vol. 26, No. 5, pp. 17-27, Oct. 2025
    10.7472/jksii.2025.26.5.17
    Keywords: Elderly Fall Detection, CCTV Video Analysis, Object Detection and Tracking, YOLOv8
  6. 96. Maritime Life Jacket Detection Using Sequential Lightweight Models
    Young-nam Song, Seung-gyu Kim, Tae-Ho Im, Vol. 26, No. 5, pp. 29-38, Oct. 2025
    10.7472/jksii.2025.26.5.29
    Keywords: Life-jacket Detection, YOLO11n, Dual Detection Method, Marine Safety, small-object detection
  7. 97. Enhanced DDoS Detection via Traffic Volume-based Labeling and Transfer learning
    Hyunjun Park, Insup Lee, Vol. 26, No. 4, pp. 1-8, Aug. 2025
    10.7472/jksii.2025.26.4.1
    Keywords: ddos detection, Deep Learning, Transfer Learning, traffic volume-based labeling
  8. 98. A Study on Data Augmentation Methods for Improving the Performance of Machine Learning Models in Network Attack Detection
    Taesu Kim, Dongkyoo Shin, Dongil Shin, Vol. 26, No. 3, pp. 1-7, Jun. 2025
    10.7472/jksii.2025.26.3.1
    Keywords: Network intrusion detection, data augmentation
  9. 99. DiabetesNet: Lightweight and Efficient AI-based Solution for Real-World Diabetic Foot Classification
  10. 100. A Study on Anomaly Detection Method for Ship Induction Motors Using Current Signals
    Sang-Jae Yeo, Zoo-Ho Son, Jee-Yeon Jeon, Hyung-Taek Kim, Vol. 26, No. 2, pp. 43-50, Apr. 2025
    10.7472/jksii.2025.26.2.43
    Keywords: Anomaly Detection, Machine Learning, Current signal, Induction motor, Statistical distance