A proposal of a transport system connecting demand responsive bus with mass transit. - Kazuki Uehara; Yuhei Akamine; Naruaki Toma; Moeko Nerome; Satoshi Endo (ICCE-TW, 2014)

Evaluation of a Hierarchical Cooperative Transport System Using Demand Responsive Bus on a Dynamic Simulation. - Kazuki Uehara; Yuhei Akamine; Naruaki Toma; Moeko Nerome; Satoshi Endo (IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2016)

Object detection of satellite images using multi-channel higher-order local autocorrelation. - Kazuki Uehara; Hidenori Sakanashi; Hirokazu Nosato; Masahiro Murakawa; Hiroki Miyamoto; Ryosuke Nakamura (SMC, 2017)

Object Detection in Satellite Imagery Using 2-Step Convolutional Neural Networks. - Hiroki Miyamoto; Kazuki Uehara; Masahiro Murakawa; Hidenori Sakanashi; Hirokazu Nosato; Toru Kouyama; Ryosuke Nakamura (IGARSS, 2018)

Prototype-Based Interpretation of Pathological Image Analysis by Convolutional Neural Networks. - Kazuki Uehara; Masahiro Murakawa; Hirokazu Nosato; Hidenori Sakanashi (ACPR (2), 2019)

Object Detection in Satellite Images Based on Active Learning Utilizing Visual Explanation. - Kazuki Uehara; Hirokazu Nosato; Masahiro Murakawa; Hidenori Sakanashi (ISPA, 2019)

Multi-Scale Explainable Feature Learning for Pathological Image Analysis Using Convolutional Neural Networks. - Kazuki Uehara; Masahiro Murakawa; Hirokazu Nosato; Hidenori Sakanashi (ICIP, 2020)

Explainable Feature Embedding using Convolutional Neural Networks for Pathological Image Analysis. - Kazuki Uehara; Masahiro Murakawa; Hirokazu Nosato; Hidenori Sakanashi (ICPR, 2020)

Explainable Deep Feature Embedding Using Multiple Instance Learning for Pathological Image Analysis. - Kazuki Uehara; Wataru Uegami; Hirokazu Nosato; Masahiro Murakawa; Junya Fukuoka; Hidenori Sakanashi (AAAI Spring Symposium: MAKE, 2022)

Multi-Scale Feature Aggregation Based Multiple Instance Learning for Pathological Image Classification. - Takeshi Yoshida; Kazuki Uehara; Hidenori Sakanashi; Hirokazu Nosato; Masahiro Murakawa (ICPRAM, 2023)

MSAA-Net: Multi-Scale Attention Assembler Network Based on Multiple Instance Learning for Pathological Image Analysis. - Takeshi Yoshida; Kazuki Uehara; Hidenori Sakanashi; Hirokazu Nosato; Masahiro Murakawa (ICPRAM (Revised Selected Papers), 2023)

Evidence Dictionary Network Using Multiple Instance Contrastive Learning for Explainable Pathological Image Analysis. - Kazuki Uehara; Wataru Uegami; Hirokazu Nosato; Masahiro Murakawa; Junya Fukuoka; Hidenori Sakanashi (ISBI, 2023)

Ensemble Distillation of Divergent Opinions for Robust Pathological Image Classification. - Kazuki Uehara; Wataru Uegami; Hirokazu Nosato; Masahiro Murakawa; Junya Fukuoka; Hidenori Sakanashi (EMBC, 2024)