Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Satoshi Asamizu"'
Publikováno v:
Sensors, Vol 24, Iss 10, p 3033 (2024)
In this study, we propose a classification method of expert–novice levels using a graph convolutional network (GCN) with a confidence-aware node-level attention mechanism. In classification using an attention mechanism, highlighted features may not
Externí odkaz:
https://doaj.org/article/7a6336780d5c4f858ace42ea69beccb2
Publikováno v:
IEEE Access, Vol 10, Pp 12503-12509 (2022)
In this paper, we present refining graph representation for cross-domain recommendation (CDR) based on edge pruning considering feature distribution in a latent space. Conventional graph-based CDR methods have utilized all ratings and purchase histor
Externí odkaz:
https://doaj.org/article/04758a7b97604fb9831da81351ffa94e
Publikováno v:
2021 IEEE 10th Global Conference on Consumer Electronics (GCCE).
Publikováno v:
2021 IEEE International Conference on Image Processing (ICIP).
Autor:
Nobuhiro Suzuki, Takumi Kayukawa, Shunsuke Yajima, Satoshi Asamizu, Hinoki Oikawa, Motohiro Tomizawa, Kenji Shimomura
Publikováno v:
Journal of Asia-Pacific Entomology. 22:916-920
Plant-derived compounds such as essential oils (EOs) are sources of protection for stored products. In some cases, inactive ingredients that co-occur with EOs may render them more toxic or less desirable. Thus, there has been a shift away from extrac
Publikováno v:
International Workshop on Advanced Imaging Technology (IWAIT) 2021.
This paper presents cross-domain recommendation based on multilayer graph analysis using subgraph representation. The proposed method constructs two graphs in source and target domains utilizing user-item embedding and trains link relationships betwe
Publikováno v:
GCCE
This paper presents cross-domain recommendation via multi-layer graph analysis using user-item embedding. The proposed method constructs two graphs in source and target domains utilizing user-item embedding, respectively. By training relationship bet
Publikováno v:
International Workshop on Advanced Image Technology (IWAIT) 2019.
Publikováno v:
International Workshop on Advanced Image Technology (IWAIT) 2019.
Publikováno v:
LifeTech
This paper presents a method for estimating emotions evoked by watching images based on multiple visual features considering relationship with gaze information. The proposed method obtains multiple visual features from multiple middle layers of a Con