Presentation 2021-09-17
Identifying Design Problems of Presentation Slides using a Bimodal Neural Network
Shengzhou Yi, Junichiro Matsugami, Toshihiko Yamasaki,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Although millions of presentation slides are created every day in business and academia, there are only a limited number of support systems that are helpful to assess the slides. In this study, a bimodal neural network, using visual and structural features, is proposed to identify the design problem of presentation slides. For such a purpose, over two thousand slides were collected for training the model. We summarized ten checkpoints, which are common problems in slide design. The dataset faces an imbalanced distribution, because only a small part of the samples had corresponding design problems. To address the class imbalance issue, several sampling methods are applied to improve the prediction performance. Furthermore, we also use transfer and multi-task learning to enhance the bimodal neural network. The optimal combination of these machine-learning methods helps the proposed network achieve an average accuracy of 81.79%.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Presentation Slide / Class Imbalance / Multi-Task Learning / Transfer Learning
Paper # MVE2021-12
Date of Issue 2021-09-10 (MVE)

Conference Information
Committee MVE
Conference Date 2021/9/17(2days)
Place (in Japanese) (See Japanese page)
Place (in English) Online
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair Masayuki Ihara(RIKEN)
Vice Chair Kiyoshi Kiyokawa(NAIST)
Secretary Kiyoshi Kiyokawa(Oosaka Inst. of Tech.)
Assistant Naoya Isoyama(NAIST) / Takenori Hara(DNP) / Mitsuhiro Goto(NTT)

Paper Information
Registration To Technical Committee on Media Experience and Virtual Environment
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Identifying Design Problems of Presentation Slides using a Bimodal Neural Network
Sub Title (in English)
Keyword(1) Presentation Slide
Keyword(2) Class Imbalance
Keyword(3) Multi-Task Learning
Keyword(4) Transfer Learning
1st Author's Name Shengzhou Yi
1st Author's Affiliation The University of Tokyo(UTokyo)
2nd Author's Name Junichiro Matsugami
2nd Author's Affiliation Rubato Co., Ltd.(Rubato)
3rd Author's Name Toshihiko Yamasaki
3rd Author's Affiliation The University of Tokyo(UTokyo)
Date 2021-09-17
Paper # MVE2021-12
Volume (vol) vol.121
Number (no) MVE-179
Page pp.pp.21-26(MVE),
#Pages 6
Date of Issue 2021-09-10 (MVE)