Hideaki Hayashi | DeepAI

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Featured Co-authors

Seiichi Uchida
60 publications
Hideki Nakayama
44 publications
Brian Kenji Iwana
28 publications
Ryoma Bise
20 publications
Joonho Lee
17 publications
Leonardo Rundo
16 publications
Changhee Han
15 publications
Giancarlo Mauri
13 publications
Kumar Shridhar
13 publications
Tomohiro Hayase
10 publications
Daichi Haraguchi
7 publications

∙ 06/21/2023

Analyzing Font Style Usage and Contextual Factors in Real Images

There are various font styles in the world. Different styles give differ...

0 Naoya Yasukochi, et al. ∙

∙ 05/10/2023

A Hybrid of Generative and Discriminative Models Based on the Gaussian-coupled Softmax Layer

Generative models have advantageous characteristics for classification t...

0 Hideaki Hayashi, et al. ∙

∙ 08/05/2022

Deep Bayesian Active-Learning-to-Rank for Endoscopic Image Data

Automatic image-based disease severity estimation generally uses discret...

0 Takeaki Kadota, et al. ∙

∙ 11/06/2021

Order-Guided Disentangled Representation Learning for Ulcerative Colitis Classification with Limited Labels

Ulcerative colitis (UC) classification, which is an important task for e...

0 Shota Harada, et al. ∙

∙ 03/17/2021

Meta-learning of Pooling Layers for Character Recognition

In convolutional neural network-based character recognition, pooling lay...

8 Takato Otsuzuki, et al. ∙

∙ 02/26/2021

Layer-Wise Interpretation of Deep Neural Networks Using Identity Initialization

The interpretability of neural networks (NNs) is a challenging but essen...

0 Shohei Kubota, et al. ∙

∙ 09/27/2020

Handwriting Prediction Considering Inter-Class Bifurcation Structures

Temporal prediction is a still difficult task due to the chaotic behavio...

0 Masaki Yamagata, et al. ∙

∙ 05/06/2020

Regularized Pooling

In convolutional neural networks (CNNs), pooling operations play importa...

0 Takato Otsuzuki, et al. ∙

∙ 11/14/2019

SDGM: Sparse Bayesian Classifier Based on a Discriminative Gaussian Mixture Model

In probabilistic classification, a discriminative model based on Gaussia...

22 Hideaki Hayashi, et al. ∙

∙ 11/14/2019

A Recurrent Probabilistic Neural Network with Dimensionality Reduction Based on Time-series Discriminant Component Analysis

This paper proposes a probabilistic neural network developed on the basi...

50 Hideaki Hayashi, et al. ∙

∙ 06/14/2019

Modality Conversion of Handwritten Patterns by Cross Variational Autoencoders

This research attempts to construct a network that can convert online an...

1 Taichi Sumi, et al. ∙

∙ 05/31/2019

Combining Noise-to-Image and Image-to-Image GANs: Brain MR Image Augmentation for Tumor Detection

Convolutional Neural Networks (CNNs) can achieve excellent computer-assi...

0 Changhee Han, et al. ∙

∙ 05/30/2019

A Trainable Multiplication Layer for Auto-correlation and Co-occurrence Extraction

In this paper, we propose a trainable multiplication layer (TML) for a n...

0 Hideaki Hayashi, et al. ∙

∙ 05/29/2019

GlyphGAN: Style-Consistent Font Generation Based on Generative Adversarial Networks

In this paper, we propose GlyphGAN: style-consistent font generation bas...

0 Hideaki Hayashi, et al. ∙

∙ 05/26/2019

ProbAct: A Probabilistic Activation Function for Deep Neural Networks

Activation functions play an important role in the training of artificia...

0 Joonho Lee, et al. ∙

∙ 05/17/2019

Biosignal Generation and Latent Variable Analysis with Recurrent Generative Adversarial Networks

The effectiveness of biosignal generation and data augmentation with bio...

0 Shota Harada, et al. ∙

∙ 03/29/2019

Infinite Brain MR Images: PGGAN-based Data Augmentation for Tumor Detection

Due to the lack of available annotated medical images, accurate computer...

22 Changhee Han, et al. ∙

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