◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

M. Nakanishi

3 papers hereh-index 203.3k citations74 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author2

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.LG1
  • eess.IV1
  • q-bio.NC1
same name
  • M. Nakanishi — 2 papers, h 9

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedBoosting Template-based SSVEP Decoding by Cross-domain Transfer Learning

79 citations · 82 across the 2 of their papers we have counts for

collaborators

3 papers

eess.IV2021★ 3 cited

Anomaly Detection By Autoencoder Based On Weighted Frequency Domain Loss

Masaki Nakanishi, Kazuki Sato, Hideo Terada

In image anomaly detection, Autoencoders are the popular methods that reconstruct the input image that might contain anomalies and output a clean image with no abnormalities. These…

cs.LG2021★ 79 cited

Boosting Template-based SSVEP Decoding by Cross-domain Transfer Learning

Kuan-Jung Chiang, Chun-Shu Wei, Masaki Nakanishi +1

Objective: This study aims to establish a generalized transfer-learning framework for boosting the performance of steady-state visual evoked potential (SSVEP)-based brain-computer…

q-bio.NC2018

Cross-Subject Transfer Learning Improves the Practicality of Real-World Applications of Brain-Computer Interfaces

Kuan-Jung Chiang, Chun-Shu Wei, Masaki Nakanishi +1

Steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) have shown its robustness in facilitating high-efficiency communication. State-of-the-art traini…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.