Prediction of Tropical Storms Using Self-organizing Incremental Neural Networks and Error Evaluation. - Wonjik Kim; Osamu Hasegawa (ICONIP (3), 2017)

Improved Kernel Density Estimation Self-organizing Incremental Neural Network to Perform Big Data Analysis. - Wonjik Kim; Osamu Hasegawa (ICONIP (2), 2018)

Time Series Prediction of Tropical Storm Trajectory Using Self-Organizing Incremental Neural Networks and Error Evaluation. - Wonjik Kim; Osamu Hasegawa (J. Adv. Comput. Intell. Intell. Informatics, 2018)

Simultaneous Forecasting of Meteorological Data Based on a Self-Organizing Incremental Neural Network. - Wonjik Kim; Osamu Hasegawa (J. Adv. Comput. Intell. Intell. Informatics, 2018)

Automatic Labeled LiDAR Data Generation based on Precise Human Model. - Wonjik Kim; Masayuki Tanaka 001; Masatoshi Okutomi; Yoko Sasaki (ICRA, 2019)

Automatic Labeled LiDAR Data Generation and Distance-Based Ensemble Learning for Human Segmentation. - Wonjik Kim; Masayuki Tanaka 001; Masatoshi Okutomi; Yoko Sasaki (IEEE Access, 2019)

Adaptive Future Frame Prediction with Ensemble Network. - Wonjik Kim; Masayuki Tanaka 001; Masatoshi Okutomi; Yoko Sasaki (ICPR Workshops (7), 2020)

Human Segmentation with Dynamic LiDAR Data. - Tao Zhong; Wonjik Kim; Masayuki Tanaka 001; Masatoshi Okutomi (ICPR, 2020)

Learning-Based Human Segmentation and Velocity Estimation Using Automatic Labeled LiDAR Sequence for Training. - Wonjik Kim; Masayuki Tanaka 001; Masatoshi Okutomi; Yoko Sasaki (IEEE Access, 2020)

Unsupervised Learning of Image Segmentation Based on Differentiable Feature Clustering. - Wonjik Kim; Asako Kanezaki; Masayuki Tanaka 001 (IEEE Trans. Image Process., 2020)

AUAAC: Area Under Accuracy-Accuracy Curve for Evaluating Out-of-Distribution Detection. - Wonjik Kim; Masayuki Tanaka 001; Masatoshi Okutomi (PSIVT, 2023)

Deformable element-wise dynamic convolution. - Wonjik Kim; Masayuki Tanaka 001; Yoko Sasaki; Masatoshi Okutomi (J. Electronic Imaging, 2023)

Kernel-Level Dropout for the Convolution Process in Deep Learning. - Wonjik Kim (MCSoC, 2024)

A Random Focusing Method with Jensen-Shannon Divergence for Improving Deep Neural Network Performance Ensuring Architecture Consistency. - Wonjik Kim (Neural Process. Lett., 2024)

Emotion recognition and forecasting from wearable data via cluster-guided attention with cross-species pretraining. - Wonjik Kim; Gaku Kutsuzawa; Michiyo Maruyama (Intell. Syst. Appl., 2025)

Deep metric learning with in-batch feature vector constraints and unsupervised label integration. - Wonjik Kim (Evol. Intell., 2025)