Kanata Suzuki

According to our database, Kanata Suzuki authored at least 24 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Interactively Robot Action Planning with Uncertainty Analysis and Active Questioning by Large Language Model.

Kazuki Hori, Kanata Suzuki, Tetsuya Ogata

Proceedings of the IEEE/SICE International Symposium on System Integration, 2024

2023

Realtime Motion Generation with Active Perception Using Attention Mechanism for Cooking Robot.

Namiko Saito, Mayu Hiramoto, Ayuna Kubo, Kanata Suzuki, Hiroshi Ito, Shigeki Sugano, Tetsuya Ogata

CoRR, 2023

Deep Predictive Learning : Motion Learning Concept inspired by Cognitive Robotics.

Kanata Suzuki, Hiroshi Ito, Tatsuro Yamada, Kei Kase, Tetsuya Ogata

CoRR, 2023

Machine Learning Approach for Frozen Tuna Freshness Inspection Using Low-Frequency A-Mode Ultrasound.

Akira Sakai, Masafumi Yagi, Suguru Yasutomi, Kazuki Mizuno, Kanata Suzuki, Keiichi Goto

IEEE Access, 2023

2022

Learning Bidirectional Translation Between Descriptions and Actions With Small Paired Data.

Minori Toyoda, Kanata Suzuki, Yoshihiko Hayashi, Tetsuya Ogata

IEEE Robotics Autom. Lett., 2022

Three approaches to facilitate invariant neurons and generalization to out-of-distribution orientations and illuminations.

Akira Sakai, Taro Sunagawa, Spandan Madan, Kanata Suzuki, Takashi Katoh, Hiromichi Kobashi, Hanspeter Pfister, Pawan Sinha, Xavier Boix, Tomotake Sasaki

Neural Networks, 2022

Buttoning Task with a Dual-Arm Robot: An Exploratory Study on a Marker-based Algorithmic Method and Marker-less Machine Learning Methods.

Wakana Fujii, Kanata Suzuki, Tomoki Ando, Ai Tateishi, Hiroki Mori, Tetsuya Ogata

Proceedings of the IEEE/SICE International Symposium on System Integration, 2022

2021

Development of a Basic Educational Kit for Robotic System with Deep Neural Networks.

Momomi Kanamura, Kanata Suzuki, Yuki Suga, Tetsuya Ogata

Sensors, 2021

Embodying Pre-Trained Word Embeddings Through Robot Actions.

Minori Toyoda, Kanata Suzuki, Hiroki Mori, Yoshihiko Hayashi, Tetsuya Ogata

IEEE Robotics Autom. Lett., 2021

Compensation for Undefined Behaviors During Robot Task Execution by Switching Controllers Depending on Embedded Dynamics in RNN.

Kanata Suzuki, Hiroki Mori, Tetsuya Ogata

IEEE Robotics Autom. Lett., 2021

Three approaches to facilitate DNN generalization to objects in out-of-distribution orientations and illuminations: late-stopping, tuning batch normalization and invariance loss.

Akira Sakai, Taro Sunagawa, Spandan Madan, Kanata Suzuki, Takashi Katoh, Hiromichi Kobashi, Hanspeter Pfister, Pawan Sinha, Xavier Boix, Tomotake Sasaki

CoRR, 2021

Annotation Cost Reduction of Stream-based Active Learning by Automated Weak Labeling using a Robot Arm.

Kanata Suzuki, Taro Sunagawa, Tomotake Sasaki, Takashi Katoh

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

In-air Knotting of Rope using Dual-Arm Robot based on Deep Learning.

Kanata Suzuki, Momomi Kanamura, Yuki Suga, Hiroki Mori, Tetsuya Ogata

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

2020

Classification of glomerular pathological findings using deep learning and nephrologist-AI collective intelligence approach.

Eiichiro Uchino, Kanata Suzuki, Noriaki Sato, Ryosuke Kojima, Yoshinori Tamada, Shusuke Hiragi, Hideki Yokoi, Nobuhiro Yugami, Sachiko Minamiguchi, Hironori Haga, Motoko Yanagita, Yasushi Okuno

Int. J. Medical Informatics, 2020

Undefined-behavior guarantee by switching to model-based controller according to the embedded dynamics in Recurrent Neural Network.

Kanata Suzuki, Hiroki Mori, Tetsuya Ogata

CoRR, 2020

A Multi-task Learning Framework for Grasping-Position Detection and Few-Shot Classification.

Yasuto Yokota, Kanata Suzuki, Yuzi Kanazawa, Tomoyoshi Takebayashi

Proceedings of the 2020 IEEE/SICE International Symposium on System Integration, 2020

Online Self-Supervised Learning for Object Picking: Detecting Optimum Grasping Position using a Metric Learning Approach.

Kanata Suzuki, Yasuto Yokota, Yuzi Kanazawa, Tomoyoshi Takebayashi

Proceedings of the 2020 IEEE/SICE International Symposium on System Integration, 2020

HATSUKI : An anime character like robot figure platform with anime-style expressions and imitation learning based action generation.

Pin-Chu Yang, Mohammed Al-Sada, Chang-Chieh Chiu, Kevin Kuo, Tito Pradhono Tomo, Kanata Suzuki, Nelson Yalta, Kuo-Hao Shu, Tetsuya Ogata

Proceedings of the 29th IEEE International Conference on Robot and Human Interactive Communication, 2020

Stable Deep Reinforcement Learning Method by Predicting Uncertainty in Rewards as a Subtask.

Kanata Suzuki, Tetsuya Ogata

Proceedings of the Neural Information Processing - 27th International Conference, 2020

2018

Motion Switching With Sensory and Instruction Signals by Designing Dynamical Systems Using Deep Neural Network.

Kanata Suzuki, Hiroki Mori, Tetsuya Ogata

IEEE Robotics Autom. Lett., 2018

Put-in-Box Task Generated from Multiple Discrete Tasks by aHumanoid Robot Using Deep Learning.

Kei Kase, Kanata Suzuki, Pin-Chu Yang, Hiroki Mori, Tetsuya Ogata

Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

2017

Repeatable Folding Task by Humanoid Robot Worker Using Deep Learning.

Pin-Chu Yang, Kazuma Sasaki, Kanata Suzuki, Kei Kase, Shigeki Sugano, Tetsuya Ogata

IEEE Robotics Autom. Lett., 2017

Online Motion Generation with Sensory Information and Instructions by Hierarchical RNN.

Kanata Suzuki, Hiroki Mori, Tetsuya Ogata

CoRR, 2017

2015

Efficient Motor Babbling Using Variance Predictions from a Recurrent Neural Network.

Kuniyuki Takahashi, Kanata Suzuki, Tetsuya Ogata, Hadi Tjandra, Shigeki Sugano

Proceedings of the Neural Information Processing - 22nd International Conference, 2015