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Deep Sensing for Compressive Video Acquisition
A camera captures multidimensional information of the real world by convolving it into two dimensions using a sensing matrix. The …
Michitaka Yoshida
,
Akihiko Torii
,
Masatoshi Okutomi
,
Rin Ichiro Taniguchi
,
Hajime Nagahara
,
Yasushi Yagi
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Depth Quality Improvement with a 607 MHz Time-Compressive Computational Pseudo-dToF CMOS Image Sensor
In this paper, we present a prototype pseudo-direct time-of-flight (ToF) CMOS image sensor, achieving high distance accuracy, …
Anh Ngoc Pham
,
Ibrahim Thoriq
,
Keita Yasutomi
,
Shoji Kawahito
,
Hajime Nagahara
,
Keiichiro Yagi Kagawa
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Development of a vertex finding algorithm using Recurrent Neural Network
Deep learning is a rapidly-evolving technology with the possibility to significantly improve the physics reach of collider experiments. …
Kiichi Goto
,
Taikan Suehara
,
Tamaki Yoshioka
,
Masakazu Kurata
,
Hajime Nagahara
,
Yuta Nakashima
,
Noriko Takemura
,
Masako Iwasaki
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Human-Imperceptible Identification With Learnable Lensless Imaging
Lensless imaging protects visual privacy by capturing heavily blurred images that are imperceptible for humans to recognize the subject …
Thuong Nguyen Canh
,
Trung Thanh Ngo
,
Hajime Nagahara
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Information Extraction from Public Meeting Articles
Public meeting articles are the key to understanding the history of public opinion and public sphere in Australia. Information …
Felix Giovanni Virgo
,
Chenhui Chu
,
Takaya Ogawa
,
Koji Tanaka
,
Kazuki Ashihara
,
Yuta Nakashima
,
Noriko Takemura
,
Hajime Nagahara
,
Takao Fujikawa
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Anonymous identity sampling and reusable synthesis for sensitive face camouflage
An increasing amount of face images are being captured, shared, or applied in various applications. These images usually contain lots …
Zhenzhong Kuang
,
Longbin Teng
,
Xingchi He
,
Jiajun Ding
,
Yuta Nakashima
,
Noboru Babaguchi
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Corpus Construction for Historical Newspapers: A Case Study on Public Meeting Corpus Construction Using OCR Error Correction
Koji Tanaka
,
Chenhui Chu
,
Tomoyuki Kajiwara
,
Yuta Nakashima
,
Noriko Takemura
,
Hajime Nagahara
,
Takao Fujikawa
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Depthwise spatio-temporal STFT convolutional neural networks for human action recognition
Conventional 3D convolutional neural networks (CNNs) are computationally expensive, memory intensive, prone to overfitting, and most …
Sudhakar Kumawat
,
Manisha Verma
,
Yuta Nakashima
,
Shanmuganathan Raman
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Human--Machine Interfaces Based on Bioelectric Signals: A Narrative Review with a Novel System Proposal
Bioelectric signals such as electromyogram (EMG) and electroencephalogram (EEG) reflect human internal states and intended actions, and …
Hideaki Hayashi
,
Toshio Tsuji
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Match them up: visually explainable few-shot image classification
Few-shot learning (FSL) approaches, mostly neural network-based, assume that pre-trained knowledge can be obtained from base (seen) …
Bowen Wang
,
Liangzhi Li
,
Manisha Verma
,
Yuta Nakashima
,
Ryo Kawasaki
,
Hajime Nagahara
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