Digital Library

1. 1. Performance Analysis and Improvement of AI model for Radar Signal Modulation Type Classification based on Data Preprocessing
   Juhyoung Sung, Kiwon Kwon, Kyoungwon Park, Vol. 26, No. 4, pp. 31-39, Aug. 2025
   10.7472/jksii.2025.26.4.31
   Keywords: Artificial intelligence, CNN, Data Preprocessing, modulation type classification, Radar signal, STFT, WVD
2. 2. DiabetesNet: Lightweight and Efficient AI-based Solution for Real-World Diabetic Foot Classification
   Jeong-Eun Moon, Yong-Jin Cho, Se-Yeol Rhyou, Sang-Hoon Hong, Vol. 26, No. 2, pp. 167-178, Apr. 2025
   10.7472/jksii.2025.26.2.167
   Keywords: Diabetic Foot Classification, AI-Powered Healthcare, Object Detection, Convolutional Neural Network (CNN), explainable artificial intelligence (XAI)
3. 3. Research on DNS DRDoS Detection Methods Using CNN
   Hoon Shin, Jaeyeong Jeong, Kyu-min Cho, Jae-il Lee, Dong-kyoo Shin, Vol. 25, No. 6, pp. 131-145, Dec. 2024
   10.7472/jksii.2024.25.6.131
   Keywords: AI Security, Artificial intelligence, Machine Learning, Deep Learning, CNN, DDoS, DrDoS, image processing, Image Classification
4. 4. Data Efficient Image Classification for Retinal Disease Diagnosis
   Honggu Kang, Huigyu Yang, Moonseong Kim, Hyunseung Choo, Vol. 25, No. 3, pp. 19-25, Jun. 2024
   10.7472/jksii.2024.25.3.19
   Keywords: Ocular disease diagnosis and classification, CFI, CNN, Deep Learning, Artificial intelligence
5. 5. A Comparison Study of RNN, CNN, and GAN Models in Sequential Recommendation
   Ji Hyung Yoon, Jaewon Chung, Beakcheol Jang, Vol. 23, No. 4, pp. 21-33, Aug. 2022
   10.7472/jksii.2022.23.4.21
   Keywords: Recommender System, RNN, CNN, GAN, Deep Learning, sequence modeling
6. 6. A Research on Network Intrusion Detection based on Discrete Preprocessing Method and Convolution Neural Network
   JiHoon Yoo, Byeongjun Min, Sangsoo Kim, Dongil Shin, Dongkyoo Shin, Vol. 22, No. 2, pp. 29-39, Apr. 2021
   10.7472/jksii.2021.22.2.29
   Keywords: NSL-KDD, Network intrusion detection, CNN, Discretization of Continuous
7. 7. Empirical Comparison of Deep Learning Networks on Backbone Method of Human Pose Estimation
   Beanbonyka Rim, Junseob Kim, Yoo-Joo Choi, Min Hong, Vol. 21, No. 5, pp. 21-29, Oct. 2020
   10.7472/jksii.2020.21.5.21
   Keywords: Deep Learning, Human Pose Estimation, CNN, VGG, ResNet
8. 8. A Study on Model for Drivable Area Segmentation based on Deep Learning
   Hyo-jin Jeon, Soo-sun Cho, Vol. 20, No. 5, pp. 105-111, Oct. 2019
   10.7472/jksii.2019.20.5.105
   Keywords: Drivable area segmentation, segmentation, Deep Learning, DeepLab V3+, Mask R-CNN, BDD Dataset
9. 9. Pedestrian Classification using CNN's Deep Features and Transfer Learning
   Soyoung Chung, Min Gyo Chung, Vol. 20, No. 4, pp. 91-102, Aug. 2019
   10.7472/jksii.2019.20.4.91
   Keywords: Pedestrian Classification, Transfer Learning, Deep Features, CNN, INRIA Person Data Set
10. 10. A Study on the Pipe Position Estimation in GPR Images Using Deep Learning Based Convolutional Neural Network
    Jihun Chae, Hyoung-yong Ko, Byoung-gil Lee, Namgi Kim, Vol. 20, No. 4, pp. 39-46, Aug. 2019
    10.7472/jksii.2019.20.4.39
    Keywords: sink holes, pipe, GPR, Image recognition, underground detection, CNN, deep-learning