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Titlebook: Neural Information Processing; 28th International C Teddy Mantoro,Minho Lee,Achmad Nizar Hidayanto Conference proceedings 2021 Springer Nat

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发表于 2025-3-21 18:11:10 | 显示全部楼层 |阅读模式
书目名称Neural Information Processing
副标题28th International C
编辑Teddy Mantoro,Minho Lee,Achmad Nizar Hidayanto
视频video
丛书名称Communications in Computer and Information Science
图书封面Titlebook: Neural Information Processing; 28th International C Teddy Mantoro,Minho Lee,Achmad Nizar Hidayanto Conference proceedings 2021 Springer Nat
描述The two-volume set CCIS 1516 and 1517 constitutes thoroughly refereed short papers presented at the 28th International Conference on Neural Information Processing, ICONIP 2021, held in Sanur, Bali, Indonesia, in December 2021.* The volume also presents papers from the workshop on Artificial Intelligence and Cyber Security, held during the ICONIP 2021. .The 176 short and workshop papers presented in this volume were carefully reviewed and selected for publication out of 1093 submissions. The papers are organized in topical sections as follows: theory and algorithms; AI and cybersecurity; cognitive neurosciences; human centred computing; advances in deep and shallow machine learning algorithms for biomedical data and imaging; reliable, robust, and secure machine learning algorithms; theory and applications of natural computing paradigms; applications..* The conference was held virtually due to the COVID-19 pandemic..
出版日期Conference proceedings 2021
关键词artificial intelligence; communication systems; computer networks; computer systems; computer vision; dat
版次1
doihttps://doi.org/10.1007/978-3-030-92310-5
isbn_softcover978-3-030-92309-9
isbn_ebook978-3-030-92310-5Series ISSN 1865-0929 Series E-ISSN 1865-0937
issn_series 1865-0929
copyrightSpringer Nature Switzerland AG 2021
The information of publication is updating

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发表于 2025-3-21 21:04:01 | 显示全部楼层
A Region Descriptive Pre-training Approach with Self-attention Towards Visual Question Answering as a bridge to map the text and image inputs. The addition of region description makes our model perform better against some recent state-of-the-art models. Experiments demonstrated in this paper show that our model significantly outperforms most of these models.
发表于 2025-3-22 02:12:48 | 显示全部楼层
Prediction of Inefficient BCI Users Based on Cognitive Skills and Personality TraitsThe most accurate model was based on: Spatial Ability, Visuospatial Memory, Autonomy, and Vividness of Visual Imagery. Further correlation analyses showed that a novice user’s . suppression during a MI-BCI task can be predicted based on their visuospatial memory, as measured by the Design Organization Test (DOT).
发表于 2025-3-22 06:54:52 | 显示全部楼层
UED: A Unified Encoder Decoder Network for Visual DialogD is unified in that (1) it fully exploiting the interaction between different modalities to support answer ranking and generation in a single transformer based model, and (2) it uses the answers as anchors to facilitate both two settings. We evaluate the proposed UED on the VisDial dataset, where our model outperforms the state-of-the-art.
发表于 2025-3-22 09:35:31 | 显示全部楼层
发表于 2025-3-22 13:48:56 | 显示全部楼层
Conference proceedings 2021n Processing, ICONIP 2021, held in Sanur, Bali, Indonesia, in December 2021.* The volume also presents papers from the workshop on Artificial Intelligence and Cyber Security, held during the ICONIP 2021. .The 176 short and workshop papers presented in this volume were carefully reviewed and selected
发表于 2025-3-22 17:28:23 | 显示全部楼层
1865-0929 Information Processing, ICONIP 2021, held in Sanur, Bali, Indonesia, in December 2021.* The volume also presents papers from the workshop on Artificial Intelligence and Cyber Security, held during the ICONIP 2021. .The 176 short and workshop papers presented in this volume were carefully reviewed an
发表于 2025-3-22 22:47:44 | 显示全部楼层
Video Captioning with External Knowledge Assistance and Multi-feature Fusionain more informative video features and higher quality semantic features. Experimental results on the MSVD and MSRVTT datasets show that the proposed method can greatly improve the caption diversity and model performance, surpass all previous models in all evaluation metrics, and achieve the new state-of-the-art results.
发表于 2025-3-23 04:04:52 | 显示全部楼层
发表于 2025-3-23 08:06:32 | 显示全部楼层
BCI Speller on Smartphone Device with Diminutive-Sized Visual Stimulific spatial-temporal features. The results showed 96.8% of spelling accuracy with a maximum ITR of 31.6 [bits/min], which is comparable or even superior to conventional speller systems. Our study demonstrated the feasibility to create more reliable and practical BCI spelling systems in the future.
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