Fully Data-driven but Interpretable Human Behavioural Modelling with Differentiable Discrete Choice Model

Autor: Makinoshima, Fumiyasu, Mitomi, Tatsuya, Makihara, Fumiya, Segawa, Eigo

Discrete choice models are essential for modelling various decision-making processes in human behaviour. However, the specification of these models has depended heavily on domain knowledge from experts, and the fully automated but interpretable model

Externí odkaz: http://arxiv.org/abs/2412.19403

Privacy-conscious human detection using low-resolution video.

Autor: Miyazaki, Nobuhiro, Tsuji, Kentaro, Zheng, Mingxie, Nakashima, Moyuri, Matsuda, Yuji, Segawa, Eigo

Publikováno v: 2015 3rd IAPR Asian Conference on Pattern Recognition (ACPR); 2015, p326-330, 5p

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Robust active contours with insensitive parameters

Autor: Xu, Gang, Segawa, Eigo, Tsuji, Saburo

Publikováno v: In Pattern Recognition 1994 27(7):879-884

A study on the robustness of shape descriptors to common scanning artifacts

Autor: Tomislav Pribanić, Joaquim Salvi, Ferran Roure, Xavier Lladó, Josep Forest, Yago Diz

Publikováno v: MVA
© Machine Vision Applications (MVA), 2015 14th IAPR International Conference on, 2015, p.522-525
Articles publicats (D-ATC)
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Registration is a fundamental problem in a myriad of applications ranging from heritage reconstruction to industrial applications. Descriptors are an important part of the registration pipeline as well as a very active research field. However, the se

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::44c8cb0d4a81ed5f9a1e42872eb2e767
https://doi.org/10.1109/mva.2015.7153245