Conferences (English)

2024

1. Auxiliary selection: optimal selection of auxiliary tasks using deep reinforcement learning

   Hidenori Itaya, Tsubasa Hirakawa, Takayoshi Yamashita, and Hironobu Fujiyoshi

   In IIEEJ International Conference on Image Electronics and Visual Computing (IEVC), 2024
2. Class Weighted Focal Loss for Improving Class Imbalance in Semi-supervised Object Detection

   Shinichi Hoketsu, Tsubasa Hirakawa, Takayoshi Yamashita, and Hironobu Fujiyoshi

   In International Conference on Computer Vision Theory and Applications (VISAPP), 2024
3. Diverse Data Selection Considering Data Distribution for Unsupervised Continual Learning

   Naoto Hayashi, Tsubasa Hirakawa, Takayoshi Yamashita, and Hironobu Fujiyoshi

   In International Conference on Computer Vision Theory and Applications (VISAPP), 2024

2023

1. Recommending Learning Actions Using Neural Network

   Hirokazu Kohama, Yuki Ban, Tsubasa Hirakawa, Takayoshi Yamashita, and 3 more authors

   In International Conference on Computers in Education, 2023
2. BMVC

   Embedding Human Knowledge into Spatio-Temproal Attention Branch Network in Video Recognition via Temporal attention

   Saki Noguchi, Yuzhi Shi, Tsubasa Hirakawa, Takayoshi Yamashita, and 1 more author

   In British Machine Vision Conference (BMVC), 2023
3. Data Drift Detection with KS Test using Attention Map

   Tsunemi Nitta, Yuzhi Shi, Tsubasa Hirakawa, Takayoshi Yamashita, and 1 more author

   In Asian Conference on Pattern Recognition (ACPR), 2023
4. Single-Shot Pruning for Pre-trained Models: Rethinking the Importance of Magnitude Pruning

   Hirokazu Kohama, Hiroaki Minoura, Tsubasa Hirakawa, Takayoshi Yamashita, and 1 more author

   In ICCV Workshop on Resource Efficient Deep Learning for Computer Vision, 2023
5. Human-like Guidance with Gaze Estimation and Classification-based Text Generation

   Masaki Nambata, Kota Shimomura, Tsubasa Hirakawa, Takayoshi Yamashita, and 1 more author

   In IEEE International Conference on Intelligent Transportation Systems (ITSC), 2023
6. Visual Explanation for Cooperative Behavior in Multi-Agent Reinforcement Learning

   Hidenori Itaya, Tom Sagawa, Tsubasa Hirakawa, Takayoshi Yamashita, and 1 more author

   In International Joint Conference on Neural Networks (IJCNN), 2023
7. Analyzing the Accuracy, Representations, and Explainability of Various Loss Functions for Deep Learning

   Tenshi Ito, Hiroki Adachi, Tsubasa Hirakawa, Takayoshi Yamashita, and 1 more author

   In International Joint Conference on Neural Networks (IJCNN), 2023
8. Potential Risk Estimation with Single Monocular Camera

   Kota Shimomura, Hiroki Adachi, Tsubasa Hirakawa, Takayoshi Yamashita, and 3 more authors

   In CVPR workshop on Secure and Safe Autonomous Driving (SSAD), 2023
9. Learning from AI: An Interactive Learning Method Using a DNN Model Incorporating Expert Knowledge as a Teacher

   Kohei Hattori, Hironobu Fujiyoshi, Takayoshi Yamashita, and Tsubasa Hirakawa

   In International Conference on Artificial Intelligence in Education (AIED), 2023
10. ICLR

    This Looks Like It Rather Than That: ProtoKNN For Similarity-Based Classifiers

    Yuki Ukai, Tsubasa Hirakawa, Takayoshi Yamashita, and Hironobu Fujiyoshi

    In International Conference on Learning Representations (ICLR), 2023
11. Complement Objective Mining Branch for Optimizing Attention Map

    Takaaki Iwayoshi, Hiroki Adachi, Tsubasa Hirakawa, Takayoshi Yamashita, and 1 more author

    In International Conference on Computer Vision Theory and Applications (VISAPP), 2023
12. Masking and Mixing Adversarial Training

    Hiroki Adachi, Tsubasa Hirakawa, Takayoshi Yamashita, Hironobu Fujiyoshi, and 2 more authors

    In International Conference on Computer Vision Theory and Applications (VISAPP), 2023
13. Understanding of Feature Representation in Convolutional Neural Networks and Vision Transformer

    Hiroaki Minoura, Tsubasa Hirakawa, Takayoshi Yamashita, and Hironobu Fujiyoshi

    In International Conference on Computer Vision Theory and Applications (VISAPP), 2023
14. 1D-SalsaSAN: Semantic Segmentation of LiDAR Point Cloud with Self-Attention

    Takahiro Suzuki, Tsubasa Hirakawa, Takayoshi Yamashita, and Hironobu Fujiyoshi

    In International Conference on Computer Vision Theory and Applications (VISAPP), 2023

2022

1. Solving the Deadlock Problem with Deep Reinforcement Learning Using Information from Multiple Vehicles

   Tsuyoshi Goto, Hidenori Itaya, Tsubasa Hirakawa, Takayoshi Yamashita, and 1 more author

   In IEEE Intelligent Vehicles Symposium (IV), 2022
2. Quantification of mimicry resemblance in butterflies using feature extractor of deep neural network

   Kai Amino, Tsubasa Hirakawa, Masaya Yago, and Takashi Matsuo

   In Congress of Europian Society for Evolutionary Biology (ESEB), 2022
3. Forest-Related SDG Issues Monitoring for Data-Scarce Regions Employing Machine Learning and Remote Sensing - A Case Study for Ena City, Japan

   Anh Phan, Kiyoshi Takejima, Tsubasa Hirakawa, and Hiromichi Fukui

   In IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2022
4. Collision Prediction and Visual Explanation Generation Using Structural Knowledge in Object Placement Tasks

   Haruka Matsuo, Shumpei Hatahaka, Arisa Ueda, Tsubasa Hirakawa, and 3 more authors

   In IROS, late breaking results poster, 2022
5. ACCV

   Visual Explanation Generation Based on Lambda Attention Branch Networks

   Tsumugi Iida, Takumi Komatsu, Kanta Kaneda, Tsubasa Hirakawa, and 3 more authors

   In Asian Conference on Computer Vision (ACCV), 2022
6. ECCV

   Deep Ensemble Learning by Diverse Knowledge Distillation for Fine-Grained Object Classification

   Naoki Okamoto, Tsubasa Hirakawa, Takayoshi Yamashita, and Hironobu Fujiyoshi

   In European Conference on Computer Vision, 2022

   arXiv Code
7. Class-Wise FM-NMS for Knowledge Distillation of Object Detection

   Lyuzhuang Liu, Tsubasa Hirakawa, Takayoshi Yamashita, and Hironobu Fujiyoshi

   In IEEE International Conference on Image Processing (ICIP), 2022
8. Action Spotting in Soccer Videos Using Multiple Scene Encoders

   Yuzhi Shi, Hiroaki Minoura, Takayoshi Yamashita, Tsubasa Hirakawa, and 4 more authors

   In International Conference on Pattern Recognition (ICPR), 2022
9. Refining Design Spaces in Knowledge Distillation for Deep Collaborative Learning

   Sachi Iwata, Soma Minami, Tsubasa Hirakawa, Takayoshi Yamashita, and 1 more author

   In International Conference on Pattern Recognition (ICPR), 2022

2021

1. Performance Prediction and Importance Analysis Using Transformer

   Akiyoshi Satake, Hironobu Fujiyoshi, Takayoshi Yamashita, Tsubasa Hirakawa, and 1 more author

   In International Conference on Computers in Education Conference (ICCE), 2021
2. 1D Self-Attention Network for Point Cloud Semantic Segmentation Using Omnidirectional LiDAR

   Takahiro Suzuki, Tsubasa Hirakawa, Takayoshi Yamashita, and Hironobu Fujiyoshi

   In Asian Conference on Pattern Recognition (ACPR), 2021
3. Super-Class Mixup for Adjusting Training Data

   Shungo Fujii, Naoki Okamoto, Toshiki Seo, Tsubasa Hirakawa, and 2 more authors

   In Asian Conference on Pattern Recognition (ACPR), 2021
4. IROS

   Iterative Coarse-to-Fine 6D-Pose Estimation Using Back-propagation

   Ryosuke Araki, Kohsuke Mano, Tadanori Hirano, Tsubasa Hirakawa, and 2 more authors

   In 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021
5. Multi-Domain Semantic-Segmentation using Multi-Head Model

   Shota Masaki, Tsubasa Hirakawa, Takayoshi Yamashita, and Hironobu Fujiyoshi

   In IEEE International Intelligent Transportation Systems Conference (ITSC), 2021
6. Semantic Segmentation And Change Detection By Multi-Task U-Net

   Shungo Tsutsui, Tsubasa Hirakawa, Takayoshi Yamashita, and Hironobu Fujiyoshi

   In IEEE International Conference on Image Processing (ICIP), 2021
7. Action Spotting and Temporal Attention Analysis in Soccer Videos

   Hiroaki Minoura, Tsubasa Hirakawa, Takayoshi Yamashita, Hironobu Fujiyoshi, and 3 more authors

   In International Conference on Machine Vision and Applications (MVA), 2021
8. Attention Mining Branch for Optimizing Attention Map

   Takaaki Iwayoshi, Masahiro Mitsuhara, Masayuki Takada, Tsubasa Hirakawa, and 2 more authors

   In International Conference on Machine Vision and Applications (MVA), 2021
9. Relational Subgraph for Graph-based Path Prediction

   Masaki Miyata, Katsutoshi Shiraki, Hiroaki Minoura, Tsubasa Hirakawa, and 2 more authors

   In International Conference on Machine Vision and Applications (MVA), 2021
10. Visual Explanation using Attention Mechanism in Actor-Critic-based Deep Reinforcement Learning

    Hidenori Itaya, Tsubasa Hirakawa, Takayoshi Yamashita, Hironobu Fujiyoshi, and 1 more author

    In International Joint Conference on Neural Networks (IJCNN), 2021

    arXiv
11. Image Captioning for Near-Future Events from Vehicle Camera Images and Motion Information

    Yuki Mori, Tsubasa Hirakawa, Takayoshi Yamashita, and Hironobu Fujiyoshi

    In IEEE Intelligent Vehicles Symposium (IV), 2021
12. 3D Object Detection with Normal-map on Point Clouds

    Jishu Miao., Tsubasa Hirakawa., Takayoshi Yamashita., and Hironobu Fujiyoshi.

    In VISAPP, 2021
13. Embedding Human Knowledge into Deep Neural Network via Attention Map

    Masahiro Mitsuhara., Hiroshi Fukui., Yusuke Sakashita., Takanori Ogata., and 3 more authors

    In VISAPP, 2021

    arXiv
14. Collaborative Learning of Generative Adversarial Networks

    Takuya Tsukahara, Tsubasa Hirakawa, Takayoshi Yamashita, and Hironobu Fujiyoshi

    In VISAPP, 2021

2020

1. Correction of Seasonal Effects on VIIRS DNB Monthly Composites by Using Stable Lit Data and Regression Convolutional Neural Network

   Chuc Man Duc, Tsubasa Hirakawa, and Hiromichi Fukui

   In IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2020
2. Improving reliability of attention branch network by introducing uncertainty

   Takuya Tsukahara, Tsubasa Hirakawa, Takayoshi Yamashita, and Hironobu Fujiyoshi

   In International Conference on Pattern Recognition (ICPR), 2020
3. ACCV

   Knowledge Transfer Graph for Deep Collaborative Learning

   Soma Minami, Tsubasa Hirakawa, Takayoshi Yamashita, and Hironobu Fujiyoshi

   In Asian Conference on Computer Vision (ACCV), 2020

   arXiv Code
4. ACCV

   Spatial Temporal Attention Graph Convolutional Networks with Mechanics-Stream for Skeleton-Based Action Recognition

   Katsutoshi Shiraki, Tsubasa Hirakawa, Takayoshi Yamashita, and Hironobu Fujiyoshi

   In Asian Conference on Computer Vision (ACCV), 2020
5. Video Object Detection and Tracking based on Angle Consistency between Motion and Flow

   Toshiki Seo, Tsubasa Hirakawa, Takayoshi Yamashita, and Hironobu Fujiyoshi

   In IEEE Intelligent Vehicles Symposium (IV), 2020
6. ICRA

   MT-DSSD: Deconvolutional Single Shot Detector Using Multi Task Learning for Object Detection, Segmentation, and Grasping Detection

   Ryosuke Araki, Takeshi Onishi, Tsubasa Hirakawa, Takayoshi Yamashita, and 1 more author

   In IEEE International Conference on Robotics and Automation (ICRA), 2020
7. Simultaneous Visual Context-aware Path Prediction

   Haruka Iesaki, Tsubasa Hirakawa, Takayoshi Yamashita, Hironobu Fujiyoshi, and 3 more authors

   In VISAPP, 2020
8. Acquisition of Optimal Connection Patterns for Skeleton-based Action Recognition with Graph Convolutional Networks

   Katsutoshi Shiraki., Tsubasa Hirakawa., Takayoshi Yamashita., and Hironobu Fujiyoshi.

   In VISAPP, 2020

2019

1. Coarse-to-Fine Deep Orientation Estimator for Local Image Matching

   Yasuaki Mori, Tsubasa Hirakawa, Takayoshi Yamashita, and Hironobu Fujiyoshi

   In Asian Conference on Pattern Recognition (ACPR), 2019
2. Attention Neural Baby Talk: Captioning of Risk Factors while Driving

   Yuki Mori, Hiroshi Fukui, Tsubasa Hirakawa, Jo Nishiyama, and 2 more authors

   In IEEE Intelligent Transportation Systems Conference (ITSC), 2019
3. Automatic Creation of Path Information on Digital Map

   Haruka Iesaki, Shuhei Naruse, Tsubasa Hirakawa, Takayoshi Yamashita, and 2 more authors

   In IEEE Intelligent Transportation Systems Conference (ITSC), 2019
4. Adaptive Selection of Auxiliary Tasks in UNREAL

   Hidenori Itaya, Tsubasa Hirakawa, Takayoshi Yamasita, and Hironobu Fujiyoshi

   In IJCAI Workshop on 2nd Scaling-Up Reinforcement Learning (SURL), 2019
5. CVPR

   Attention Branch Network: Learning of Attention Mechanism for Visual Explanation

   Hiroshi Fukui, Tsubasa Hirakawa, Takayoshi Yamashita, and Hironobu Fujiyoshi

   In Computer Vision and Pattern Recognition (CVPR), 2019

   arXiv Code
6. Visual Explanation by Attention Branch Network for End-to-end Learning-based Self-driving

   Keisuke Mori, Hiroshi Fukui, Takuya Murase, Tsubasa Hirakawa, and 2 more authors

   In IEEE Intelligent Vehicles Symposium (IV), 2019
7. Scene Context-aware Rapidly-exploring Random Trees for Global Path Planning

   Tsubasa Hirakawa, Takayoshi Yamashita, and Hironobu Fujiyoshi

   In International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), 2019
8. Path Predictions using Object Attributes and Semantic Environment

   Hiroaki Minoura., Tsubasa Hirakawa., Takayoshi Yamashita., and Hironobu Fujiyoshi.

   In International Conference on Computer Vision Theory and Applications (VISAPP), 2019
9. Improved Activity Forecasting for Generating Trajectories

   Daisuke Ogawa, Toru Tamaki, Tsubasa Hirakawa, Bisser Raytchev, and 2 more authors

   In The Korea-Japan joint workshop on Frontiers of Computer Vision (FCV), 2019

   arXiv

2018

1. Survey on Vision-Based Path Prediction

   Tsubasa Hirakawa, Takayoshi Yamashita, Toru Tamaki, and Hironobu Fujiyoshi

   In International Conference on Human-Computer Interaction (HCII), 2018

   arXiv

2017

1. Travel Time-Dependent Maximum Entropy Inverse Reinforcement Learning for Seabird Trajectory Prediction

   Tsubasa Hirakawa, Takayoshi Yamashita, Ken Yoda, Toru Tamaki, and 1 more author

   In Asian Conference on Pattern Recognition (ACPR), 2017

2016

1. Discriminative Subtree Selection for NBI Endoscopic Image Labeling

   Tsubasa Hirakawa, Toru Tamaki, Takio Kurita, Bisser Raytchev, and 7 more authors

   In ACCV workshop on Mathematical and Computational Methods in Biomedical Imaging and Image Analysis, 2016
2. Transfer Learning for Endoscopic Image Classification

   Shoji Sonoyama, Toru Tamaki, Tsubasa Hirakawa, Bisser Raytchev, and 5 more authors

   In The Korea-Japan joint workshop on Frontiers of Computer Vision (FCV), 2016

   arXiv
3. Computer-Aided Colorectal Tumor Classification in NBI Endoscopy Using CNN Features

   Tamaki Toru, Shoji Sonoyama, Tsubasa Hirakawa, Bisser Raytchev, and 5 more authors

   In The Korea-Japan joint workshop on Frontiers of Computer Vision (FCV), 2016

   arXiv

2015

1. Transfer learning for Bag-of-Visual words approach to NBI endoscopic image classification

   Shoji Sonoyama, Tsubasa Hirakawa, Toru Tamaki, Takio Kurita, and 6 more authors

   In IEEE Engineering in Medicine and Biology Society (EMBC), 2015
2. Trade-off between speed and performance for colorectal endoscopic NBI image classification

   Shoji Sonoyama, Toru Tamaki, Tsubasa Hirakawa, Bisser Raytchev, and 5 more authors

   In SPIE Medical Imaging, 2015

2014

1. SVM-MRF segmentation of colorectal NBI endoscopic images

   Tsubasa Hirakawa, Tom Tamaki, Bisser Raytchev, Kazufumi Kaneda, and 4 more authors

   In IEEE Engineering in Medicine and Biology Society (EMBC), 2014

2013

1. Smoothing posterior probabilities with a particle filter of dirichlet distribution for stabilizing colorectal NBI endoscopy recognition

   Tsubasa Hirakawa, Toru Tamaki, Bisser Raytchev, Kazufumi Kaneda, and 6 more authors

   In IEEE International Conference on Image Processing (ICIP), 2013
2. Labeling colorectal NBI zoom-videoendoscope image sequences with MRF and SVM

   Tsubasa Hirakawa, Toru Tamaki, Bisser Raytchev, Kazufumi Kaneda, and 6 more authors

   In IEEE Engineering in Medicine and Biology Society (EMBC), 2013