Suguru Kanoga

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 27

Top Topics

Transfer Learning

Pattern Recognition

Top Venues

Biomed. Signal Process. Control.

Publications

Takayuki Hoshino, Suguru Kanoga, Masashi Tsubaki, Atsushi Aoyama
Comparison of fine-tuned single-source and multi-source approaches to surface electromyogram pattern recognition. Biomed. Signal Process. Control. 94 (2024)
Daisuke Yanabe, Suguru Kanoga, Vincent Frémont, Toshiyuki Murakami
Nonlinear Dynamical System Identification Under External Disturbances by Maximum a Posteriori (MAP) Estimation for Robotics. AMC (2024)
Satoshi Yagi, Mitsunori Tada, Eiji Uchibe, Suguru Kanoga, Takamitsu Matsubara, Jun Morimoto
Unsupervised Neural Motion Retargeting for Humanoid Teleoperation. CoRR (2024)
Yuji Kumano, Suguru Kanoga, Masataka Yamamoto, Hiroshi Takemura, Mitsunori Tada
Estimating Whole-Body Walking Motion from Inertial Measurement Units at Wrist and Heels Using Deep Learning. Int. J. Autom. Technol. 17 (3) (2023)
Norihisa Namura, Suguru Kanoga
The Effect of Muscle Artifact Reduction Methods on Few-channel SSVEPs during Head Movements. EMBC (2023)
Suguru Kanoga, Takayuki Hoshino, Satoshi Kamei, Takehito Kobayashi, Tsuguo Ohmori, Masaaki Uchiyama, Mitsunori Tada
Comparison of seven shallow and deep regressors in continuous blood pressure and heart rate estimation using single-channel photoplethysmograms under three evaluation cases. Biomed. Signal Process. Control. 85 (2023)
Yuto Okawa, Suguru Kanoga, Takayuki Hoshino, Tohru Nitta
Sequential Learning on sEMGs in Short- and Long-term Situations via Self-training Semi-supervised Support Vector Machine. EMBC (2022)
Suguru Kanoga, Takayuki Hoshino, Hideki Asoh
Subject-transfer framework with unlabeled data based on multiple distance measures for surface electromyogram pattern recognition. Biomed. Signal Process. Control. 74 (2022)
Suguru Kanoga, Takayuki Hoshino, Mitsunori Tada
A Style Transfer Mapping and Fine-Tuning Subject Transfer Framework Using Convolutional Neural Networks for Surface Electromyogram Pattern Recognition. ICASSP (2022)
Takayuki Hoshino, Suguru Kanoga, Masashi Tsubaki, Atsushi Aoyama
Comparing subject-to-subject transfer learning methods in surface electromyogram-based motion recognition with shallow and deep classifiers. Neurocomputing 489 (2022)
Mikito Ogino, Suguru Kanoga, Shin-Ichi Ito, Yasue Mitsukura
Semi-Supervised Learning for Auditory Event-Related Potential-Based Brain-Computer Interface. IEEE Access 9 (2021)
Suguru Kanoga, Tomoumi Takase, Takayuki Hoshino, Hideki Asoh
Time-domain Mixup Source Data Augmentation of sEMGs for Motion Recognition towards Efficient Style Transfer Mapping. EMBC (2021)
Suguru Kanoga, Takayuki Hoshino, Hideki Asoh
Semi-supervised style transfer mapping-based framework for sEMG-based pattern recognition with 1- or 2-DoF forearm motions. Biomed. Signal Process. Control. 68 (2021)
Masaki Kato, Suguru Kanoga, Takayuki Hoshino, Tadanori Fukami
Motor Imagery Classification of Finger Motions Using Multiclass CSP. EMBC (2020)
Suguru Kanoga, Takayuki Hoshino, Hideki Asoh
Subject Transfer Framework Based on Source Selection and Semi-Supervised Style Transfer Mapping for Semg Pattern Recognition. ICASSP (2020)
Suguru Kanoga, Naruki Kawai, Kota Takaoka
Deep Neural Networks for Grid-Based Elusive Crime Prediction Using a Private Dataset Obtained from Japanese Municipalities. AHFE (13) (2020)
Suguru Kanoga, Atsunori Kanemura, Hideki Asoh
Are armband sEMG devices dense enough for long-term use? - Sensor placement shifts cause significant reduction in recognition accuracy. Biomed. Signal Process. Control. 60 (2020)
Takayuki Hoshino, Suguru Kanoga, Masashi Tsubaki, Atsushi Aoyama
Analysis and Usage: Subject-to-subject Linear Domain Adaptation in sEMG Classification. EMBC (2020)
Suguru Kanoga, Atsunori Kanemura, Hideki Asoh
Multi-scale dictionary learning for ocular artifact reduction from single-channel electroencephalograms. Neurocomputing 347 (2019)
Suguru Kanoga, Atsunori Kanemura, Hideki Asoh
Corrigendum to "Multi-scale dictionary learning for ocular artifact reduction from single-channel electroencephalograms" [Neurocomputing 347 (2019) 240-250]. Neurocomputing 359 (2019)
Suguru Kanoga, Atsunori Kanemura
Assessing the effect of transfer learning on myoelectric control systems with three electrode positions. ICIT (2018)
Takayuki Hoshino, Suguru Kanoga, Atsunori Kanemura, Takeshi Ogawa
A No-Reference Metric of Cerebral Blood Flow Extraction for fNIRS Data. SMC (2018)
Suguru Kanoga, Masaki Nakanishi, Akihiko Murai, Mitsunori Tada, Atsunori Kanemura
Semi-simulation Experiments for Quantifying the Performance of SSVEP-based BCI after Reducing Artifacts from Trapezius Muscles. EMBC (2018)
Suguru Kanoga, Masashi Matsuokal, Atsunori Kanemura
Transfer Learning Over Time and Position in Wearable Myoelectric Control Systems. EMBC (2018)
Suguru Kanoga, Atsunori Kanemura, Hideki Asoh
A Comparative Study of Features and Classifiers in Single-Channel EEG-Based Motor Imagery BCI. GlobalSIP (2018)
Suguru Kanoga, Akihiko Murai, Mitsunori Tada
Exploring optimal myoelectric feature indices for forearm control strategy using robust principal component analysis. EMBC (2017)
Suguru Kanoga, Masaki Nakanishi, Yasue Mitsukura
Assessing the effects of voluntary and involuntary eyeblinks in independent components of electroencephalogram. Neurocomputing 193 (2016)
Suguru Kanoga, Yasue Mitsukura
Eye blink artifact rejection in single-channel electroencephalographic signals by complete ensemble empirical mode decomposition and independent component analysis. EMBC (2015)
Suguru Kanoga, Yasue Mitsukura
ICA-based positive semidefinite matrix templates for eye-blink artifact removal from EEG signal with single-electrode. ASCC (2015)
Suguru Kanoga, Yasue Mitsukura
Proposed blink artifacts rejection method mixing with electroencephalographic recordings using single-channel electroencephalographic recordings and non-negative matrix factorization. AMC (2014)