Search Results for author: Shin Ishii

Found 13 papers, 4 papers with code

EEGFuseNet: Hybrid Unsupervised Deep Feature Characterization and Fusion for High-Dimensional EEG with An Application to Emotion Recognition

no code implementations7 Feb 2021 Zhen Liang, Rushuang Zhou, Li Zhang, Linling Li, Gan Huang, Zhiguo Zhang, Shin Ishii

The performance of the extracted deep and low-dimensional features by EEGFuseNet is carefully evaluated in an unsupervised emotion recognition application based on three public emotion databases.

EEG Emotion Recognition

Efficient Diverse Ensemble for Discriminative Co-Tracking

no code implementations CVPR 2018 Kourosh Meshgi, Shigeyuki Oba, Shin Ishii

To remove this redundancy and have an effective ensemble learning, it is critical for the committee to include consistent hypotheses that differ from one-another, covering the version space with minimum overlaps.

Ensemble Learning

Neural Sequence Model Training via $α$-divergence Minimization

1 code implementation30 Jun 2017 Sotetsu Koyamada, Yuta Kikuchi, Atsunori Kanemura, Shin-ichi Maeda, Shin Ishii

We propose a new neural sequence model training method in which the objective function is defined by $\alpha$-divergence.

Machine Translation Translation

Active Collaborative Ensemble Tracking

no code implementations28 Apr 2017 Kourosh Meshgi, Maryam Sadat Mirzaei, Shigeyuki Oba, Shin Ishii

However, by updating all of the ensemble using a shared set of samples and their final labels, such diversity is lost or reduced to the diversity provided by the underlying features or internal classifiers' dynamics.

General Classification

Efficient Version-Space Reduction for Visual Tracking

no code implementations2 Apr 2017 Kourosh Meshgi, Shigeyuki Oba, Shin Ishii

To cope with variations of the target shape and appearance, the classifier is updated online with different samples of the target and the background.

Visual Tracking

Efficient Asymmetric Co-Tracking using Uncertainty Sampling

no code implementations31 Mar 2017 Kourosh Meshgi, Maryam Sadat Mirzaei, Shigeyuki Oba, Shin Ishii

We also introduce a budgeting mechanism which prevents the unbounded growth in the number of examples in the first detector to maintain its rapid response.

Distributional Smoothing with Virtual Adversarial Training

5 code implementations2 Jul 2015 Takeru Miyato, Shin-ichi Maeda, Masanori Koyama, Ken Nakae, Shin Ishii

We propose local distributional smoothness (LDS), a new notion of smoothness for statistical model that can be used as a regularization term to promote the smoothness of the model distribution.

Deep learning of fMRI big data: a novel approach to subject-transfer decoding

no code implementations31 Jan 2015 Sotetsu Koyamada, Yumi Shikauchi, Ken Nakae, Masanori Koyama, Shin Ishii

Our PSA successfully visualized the subject-independent features contributing to the subject-transferability of the trained decoder.

Brain Decoding

Principal Sensitivity Analysis

no code implementations21 Dec 2014 Sotetsu Koyamada, Masanori Koyama, Ken Nakae, Shin Ishii

We then visualize the PSMs to demonstrate the PSA's ability to decompose the knowledge acquired by the trained classifiers.

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