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

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書(shū)目名稱(chēng)Neural Information Processing影響因子(影響力)




書(shū)目名稱(chēng)Neural Information Processing影響因子(影響力)學(xué)科排名




書(shū)目名稱(chēng)Neural Information Processing網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱(chēng)Neural Information Processing網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱(chēng)Neural Information Processing被引頻次




書(shū)目名稱(chēng)Neural Information Processing被引頻次學(xué)科排名




書(shū)目名稱(chēng)Neural Information Processing年度引用




書(shū)目名稱(chēng)Neural Information Processing年度引用學(xué)科排名




書(shū)目名稱(chēng)Neural Information Processing讀者反饋




書(shū)目名稱(chēng)Neural Information Processing讀者反饋學(xué)科排名

Flavouring

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.

初次登臺(tái)

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).

眉毛

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.

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模仿

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

Optometrist

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

吹牛需要藝術(shù)

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.

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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.