activity
20222025
most citedCompressed Gastric Image Generation Based on Soft-Label Dataset Distillation for Medical Data Sharing

40 citations · 51 across the 8 of their papers we have counts for

collaborators

8 papers

cs.LG2025

StarMAP: Global Neighbor Embedding for Faithful Data Visualization

Koshi Watanabe, Keisuke Maeda, Takahiro Ogawa +1

Neighbor embedding is widely employed to visualize high-dimensional data; however, it frequently overlooks the global structure, e.g., intercluster similarities, thereby impeding a…

cs.CV2025

Triplet Synthesis For Enhancing Composed Image Retrieval via Counterfactual Image Generation

Kenta Uesugi, Naoki Saito, Keisuke Maeda +2

Composed Image Retrieval (CIR) provides an effective way to manage and access large-scale visual data. Construction of the CIR model utilizes triplets that consist of a reference i…

cs.CV2025

Continual Self-supervised Learning Considering Medical Domain Knowledge in Chest CT Images

Ren Tasai, Guang Li, Ren Togo +7

We propose a novel continual self-supervised learning method (CSSL) considering medical domain knowledge in chest CT images. Our approach addresses the challenge of sequential lear…

cs.CV2025

Generative Dataset Distillation Based on Self-knowledge Distillation

Longzhen Li, Guang Li, Ren Togo +3

Dataset distillation is an effective technique for reducing the cost and complexity of model training while maintaining performance by compressing large datasets into smaller, more…

cs.SD2024

MMT-BERT: Chord-aware Symbolic Music Generation Based on Multitrack Music Transformer and MusicBERT

Jinlong Zhu, Keigo Sakurai, Ren Togo +2

We propose a novel symbolic music representation and Generative Adversarial Network (GAN) framework specially designed for symbolic multitrack music generation. The main theme of s…

cs.CV20224 cited

Union-set Multi-source Model Adaptation for Semantic Segmentation

Zongyao Li, Ren Togo, Takahiro Ogawa +1

This paper solves a generalized version of the problem of multi-source model adaptation for semantic segmentation. Model adaptation is proposed as a new domain adaptation problem w…