Masayuki Tanaka

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Weighted Sigmoid Gate Unit for an Activation Function of Deep Neural Network

An activation function has crucial role in a deep neural network. A si...
10/03/2018 ∙ by Masayuki Tanaka, et al. ∙ 22 ∙ share

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Block-wise Scrambled Image Recognition Using Adaptation Network

In this study, a perceptually hidden object-recognition method is invest...
01/21/2020 ∙ by Koki Madono, et al. ∙ 17 ∙ share

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Estimation and Restoration of Compositional Degradation Using Convolutional Neural Networks

Image restoration from a single image degradation type, such as blurring...
12/23/2018 ∙ by Kazutaka Uchida, et al. ∙ 14 ∙ share

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Improving Transparency of Deep Neural Inference Process

Deep learning techniques are rapidly advanced recently, and becoming a n...
03/13/2019 ∙ by Hiroshi Kuwajima, et al. ∙ 6 ∙ share

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Learning-Based Human Segmentation and Velocity Estimation Using Automatic Labeled LiDAR Sequence for Training

In this paper, we propose an automatic labeled sequential data generatio...
03/11/2020 ∙ by Wonjik Kim, et al. ∙ 3 ∙ share

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Network Analysis for Explanation

Safety critical systems strongly require the quality aspects of artifici...
12/07/2017 ∙ by Hiroshi Kuwajima, et al. ∙ 0 ∙ share

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Non-blind Image Restoration Based on Convolutional Neural Network

Blind image restoration processors based on convolutional neural network...
09/11/2018 ∙ by Kazutaka Uchida, et al. ∙ 0 ∙ share

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Gradient-Based Low-Light Image Enhancement

A low-light image enhancement is a highly demanded image processing tech...
09/25/2018 ∙ by Masayuki Tanaka, et al. ∙ 0 ∙ share

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Automatic Labeled LiDAR Data Generation based on Precise Human Model

Following improvements in deep neural networks, state-of-the-art network...
02/14/2019 ∙ by Wonjik Kim, et al. ∙ 0 ∙ share

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Interpretation of Feature Space using Multi-Channel Attentional Sub-Networks

Convolutional Neural Networks have achieved impressive results in variou...
04/30/2019 ∙ by Masanari Kimura, et al. ∙ 0 ∙ share

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Intentional Attention Mask Transformation for Robust CNN Classification

Convolutional Neural Networks have achieved impressive results in variou...
05/07/2019 ∙ by Masanari Kimura, et al. ∙ 0 ∙ share

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Breaking Inter-Layer Co-Adaptation by Classifier Anonymization

This study addresses an issue of co-adaptation between a feature extract...
06/04/2019 ∙ by Ikuro Sato, et al. ∙ 0 ∙ share

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New Perspective of Interpretability of Deep Neural Networks

Deep neural networks (DNNs) are known as black-box models. In other word...
09/12/2019 ∙ by Masanari Kimura, et al. ∙ 0 ∙ share

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Masayuki Tanaka

Featured Co-authors

Masatoshi Okutomi

Masanari Kimura

Ikuro Sato

Hiroshi Kuwajima

Yoko Sasaki

Guoqing Liu

Kohta Ishikawa

Kazutaka Uchida

Wonjik Kim

Tetsuji Ogawa

Takashi Shibata

Weighted Sigmoid Gate Unit for an Activation Function of Deep Neural Network

Block-wise Scrambled Image Recognition Using Adaptation Network

Estimation and Restoration of Compositional Degradation Using Convolutional Neural Networks

Improving Transparency of Deep Neural Inference Process

Learning-Based Human Segmentation and Velocity Estimation Using Automatic Labeled LiDAR Sequence for Training

Network Analysis for Explanation

Non-blind Image Restoration Based on Convolutional Neural Network

Gradient-Based Low-Light Image Enhancement

Automatic Labeled LiDAR Data Generation based on Precise Human Model

Interpretation of Feature Space using Multi-Channel Attentional Sub-Networks

Intentional Attention Mask Transformation for Robust CNN Classification

Breaking Inter-Layer Co-Adaptation by Classifier Anonymization

New Perspective of Interpretability of Deep Neural Networks