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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 42  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
EMM 2021-03-05
10:20
Online Online Analysis of visual subjective evaluation for qualities of food taste using machine learning techniques
Yoshiyuki Sato (Tohoku Univ.), Kazuya Matsubara, Yuji Wada (Ritsmeikan Univ.), Nobuyuki Sakai, Satoshi Shioiri (Tohoku Univ.) EMM2020-77
In this study, we conducted an experiment to collect human subjective judgments about taste (e.g. sweetness, spiciness) ... [more] EMM2020-77
pp.58-62
HIP 2020-12-23
14:00
Online Online Analysis of human subjective evaluation using deep neural networks
Yoshiyuki Sato (Tohoku Univ.), Kazuya Matsubara, Yuji Wada (Ritsmeikan Univ.), Satoshi Shioiri (Tohoku Univ.) HIP2020-68
In this research, we constructed an deep learning model to learn and predict several different subjective judgments by h... [more] HIP2020-68
pp.77-80
HCGSYMPO
(2nd)
2020-12-15
- 2020-12-17
Online Online Analysis of Relationship between Dishes and Foods towards Serving and Arrangement Support -- Feature Analysis Focusing on Color Histogram --
Hayate Fukumoto, Mitsunori Matsushita, Ryosuke Yamanishi (Kansai Univ.)
This paper investigate relationship between foods and plates based on each color histogram and its area. The goal of thi... [more]
IE, IMQ, MVE, CQ
(Joint) [detail]
2020-03-05
14:45
Fukuoka Kyushu Institute of Technology
(Cancelled but technical report was issued)
Typicality evaluation of food-type specific presentation
Masamu Nakamura, Yasutomo Kawanishi (Nagoya Univ.), Keisuke Doman (Chukyou Univ.), Takatsugu Hirayama, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase (Nagoya Univ.) IMQ2019-49 IE2019-131 MVE2019-70
We propose a method to evaluate the typicality of a food presentation within its food-type for supporting cooking recipe... [more] IMQ2019-49 IE2019-131 MVE2019-70
pp.171-176
EMM 2020-03-05
15:35
Okinawa
(Cancelled but technical report was issued)
[Poster Presentation] A proposal for cooking asist system : Meal finder -- food recognition in refrigerator --
Masahiro Sudo, Michiharu Niimi (KIT) EMM2019-116
This paper proposes a cooking assist system which is called “Meal Finder.” For the people who feels a bother with self-c... [more] EMM2019-116
pp.75-80
MVE 2019-08-29
15:10
Aichi   [Short Paper] Typicality analysis of a food within a food category based on its appearance
Masamu Nakamura, Yasutomo Kawanishi (Nagoya Univ.), Keisuke Doman (Chukyou Univ.), Takatsugu Hirayama, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase (Nagoya Univ.) MVE2019-10
We propose a method to analyze the typicality of a food within its food category based on its appearance for supporting ... [more] MVE2019-10
pp.31-34
PRMU, BioX 2018-03-18
11:10
Tokyo   Simultaneous Learning Model of Food Image Recognition and Ingrediensts Estimation
Koyo Ito, Takao Yamanaka (Sophia Univ.) BioX2017-38 PRMU2017-174
In recent years, many health-care applications such as food diary have been developed for smart devices. It is important... [more] BioX2017-38 PRMU2017-174
pp.13-18
CQ, MVE, IE, IMQ
(Joint) [detail]
2018-03-08
14:10
Okinawa Okinawa Industry Support Center Carbohydrate Counting from Food Images
Hibiki Ikeda, Kyoko Sudo (Toho Univ.), Shigeko Kimura, Kayo Waki (Tokyo Univ.) IMQ2017-34 IE2017-126 MVE2017-76
Type 1 diabetes patients, whoes body doesn't produce enough inslin to control their blood glucose levels,
estimate th... [more]
IMQ2017-34 IE2017-126 MVE2017-76
pp.53-57
CQ, MVE, IE, IMQ
(Joint) [detail]
2018-03-08
14:30
Okinawa Okinawa Industry Support Center Improvement of taste estimation from a cooking recipe with an image -- A study on the utilization of the cooking procedure --
Yoichiro Ito (Nagoya Univ.), Keisuke Doman (Chukyo Univ.), Yasutomo Kawanishi, Takatsugu Hirayama, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase (Nagoya Univ.) IMQ2017-35 IE2017-127 MVE2017-77
Based on the image features of the dish recipe possessed by the cooking recipe, the material characteristics based on th... [more] IMQ2017-35 IE2017-127 MVE2017-77
pp.59-60
CQ, MVE, IE, IMQ
(Joint) [detail]
2018-03-09
11:15
Okinawa Okinawa Industry Support Center Generate images from food photos by Conditional GAN
Yoshifumi Ito, Ryosuke Tanno, Keiji Yanai (UEC) IMQ2017-50 IE2017-142 MVE2017-92
Making images using Generative Adversarial Network (GANs) has been actively conducted recently.
In this paper, we propo... [more]
IMQ2017-50 IE2017-142 MVE2017-92
pp.137-142
SCE 2018-01-31
10:55
Tokyo Kikai-Shinko-Kaikan Bldg. Preliminary Study on Ultra-low Field SQUID MRI Food Inspection system with Non-Resonant Circuit
Kazuma Demachi, Moriki Kabasawa, Taiga Tanaka (Toyohashi Tech.), Seiji Adachi, Keiichi Tanabe (SUSTERA), Saburo Tanaka (Toyohashi Tech.) SCE2017-34
Preliminary study on Ultra-Low Field (ULF) Magnetic Resonance Imaging (MRI) system with a high-temperature superconducto... [more] SCE2017-34
pp.15-19
MVE 2017-10-20
11:20
Hokkaido KitamiInstitute of Technology Estimating the attractiveness of a food photo using a Convolutional Neural Network
Akinori Sato (Nagoya Univ.), Keisuke Doman (Chukyo Univ.), Takatsugu Hirayama, Ichiro Ide, Yasutomo Kawanishi, Daisuke Deguchi, Hiroshi Murase (Nagoya Univ.) MVE2017-32
We have previously proposed a method for estimating the attractiveness of a food photo in order to assist a user to shoo... [more] MVE2017-32
pp.107-111
SIS, IPSJ-AVM 2017-10-13
09:30
Nara Todaiji Culture Center Food Image Enhancement Using Region Selection in RGB Color Space
Chiaki Ueda (Okayama Univ. of Science), Tadahiro Azetsu (Yamaguchi Prefectural Univ.), Noriaki Suetake, Eiji Uchino (Yamaguchi Univ.) SIS2017-29
Food images looks delicious when warm hues are vivid.
The food image acquired in low illumination environments do not o... [more]
SIS2017-29
pp.43-48
MVE 2017-09-22
10:50
Chiba Chiba Univ. Quantitative analysis on image features for the estimation of the attractiveness of food photography -- How the composition of ingredients affects the attractiveness --
Tatsumi Hattori, Keisuke Doman (Chukyo Univ.), Ichiro Ide (Nagoya Univ.), Yoshito Mekada (Chukyo Univ.) MVE2017-22
We report the results of quantitative analysis on how the composition of food ingredients affects the attractiveness of ... [more] MVE2017-22
pp.43-48
MVE, IE, CQ, IMQ
(Joint) [detail]
2017-03-06
16:35
Fukuoka Kyusyu Univ. Ohashi Campus Improvement of an attractiveness estimation method for food photos considering the appearance of main ingredients
Kazuma Takahashi (Nagoya Univ.), Keisuke Doman (Chukyo Univ.), Yasutomo Kawanishi, Takatsugu Hirayama, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase (Nagoya Univ.) IMQ2016-37 IE2016-152 MVE2016-60
In our previous research, we proposed a method for estimating the attractiveness of a food photo in order to assist a us... [more] IMQ2016-37 IE2016-152 MVE2016-60
pp.95-100
PRMU, CNR 2017-02-19
10:45
Hokkaido   Incremental Personalization of Image Classifiers
Shota Horiguchi, Sosuke Amano, Kiyoharu Aizawa (UTokyo), Makoto Ogawa (foo.log) PRMU2016-178 CNR2016-45
(To be available after the conference date) [more] PRMU2016-178 CNR2016-45
pp.149-154
DE, CEA 2016-12-01
09:30
Tokyo   Associative Food Search Triggered by User Feedback to Food Image Recognition
Sosuke Amano (Tokyo Univ./foo.log), Kiyoharu Aizawa (Tokyo Univ.), Kazuki Maeda, Masanori Kubota, Makoto Ogawa (foo.log) DE2016-22
Food diaries or diet journals are thought to be effective for improving the dietary lives of users. In this paper, we pr... [more] DE2016-22
pp.7-12
MVE 2016-10-13
17:10
Hokkaido   Accuracy improvement of food photo attractiveness estimation based on consideration of image features
Kazuma Takahashi (Nagoya Univ.), Keisuke Doman (Chukyo Univ.), Yasutomo Kawanishi, Takatsugu Hirayama, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase (Nagoya Univ.) MVE2016-12
In our previous research, we proposed a method for predicting the attractiveness of a food photo in order to assist a us... [more] MVE2016-12
pp.41-46
SIS, IPSJ-AVM 2016-09-02
10:00
Osaka Osaka Electro-Communication Univ. Saturation and Lightness Enhancement Method Considering Perceived Lightness for Food Images
Chiaki Ueda (Yamaguchi Univ.), Tadahiro Azetsu (Yamaguchi Prefectural Univ.), Noriaki Suetake, Eiji Uchino (Yamaguchi Univ.) SIS2016-24
In a food image acquired by a digital camera, its intensity and saturation components are sometimes decreased depending ... [more] SIS2016-24
pp.47-52
ITS, IE, ITE-AIT, ITE-HI, ITE-ME, ITE-MMS, ITE-CE [detail] 2016-02-23
09:45
Hokkaido Hokkaido Univ. General Food Recognition Based on Hierarchical Deep Learning with Metadata
Hokuto Kagaya, Kiyoharu Aizawa (UTokyo), Makoto Ogawa (foo.log) ITS2015-74 IE2015-116
Food image analysis is one of the key technology to record everyday meal automatically. FoodLog, the system we have been... [more] ITS2015-74 IE2015-116
pp.229-234
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