Zobrazeno 1 - 10
of 117
pro vyhledávání: '"Kazuhiro Takemoto"'
Autor:
Fairo F. Dzekashu, Abdullahi A. Yusuf, Kazuhiro Takemoto, Marcell K. Peters, H. Michael G. Lattorff, Ingolf Steffan-Dewenter, Christian W.W. Pirk
Publikováno v:
Ecological Indicators, Vol 166, Iss , Pp 112415- (2024)
Interaction network resilience can be defined as the ability of interacting organisms to maintain their functions, processes or populations after experiencing a disturbance. Studies on mutualistic interactions between plants and pollinators along env
Externí odkaz:
https://doaj.org/article/d65b41d609f44d9abfa6622377ee79c5
Autor:
Kazuhiro Takemoto
Publikováno v:
Royal Society Open Science, Vol 11, Iss 2 (2024)
As large language models (LLMs) have become more deeply integrated into various sectors, understanding how they make moral judgements has become crucial, particularly in the realm of autonomous driving. This study used the moral machine framework to
Externí odkaz:
https://doaj.org/article/eff041d221294d549258b3f127df54e0
Autor:
Kazuhiro Takemoto
Publikováno v:
Applied Sciences, Vol 14, Iss 9, p 3558 (2024)
Large Language Models (LLMs), such as ChatGPT, encounter ‘jailbreak’ challenges, wherein safeguards are circumvented to generate ethically harmful prompts. This study introduces a straightforward black-box method for efficiently crafting jailbrea
Externí odkaz:
https://doaj.org/article/1e8a613d32f84038961e75a8498dfc80
Autor:
Sasuke Fujimoto, Kazuhiro Takemoto
Publikováno v:
Frontiers in Artificial Intelligence, Vol 6 (2023)
Although ChatGPT promises wide-ranging applications, there is a concern that it is politically biased; in particular, that it has a left-libertarian orientation. Nevertheless, following recent trends in attempts to reduce such biases, this study re-e
Externí odkaz:
https://doaj.org/article/322295de23654b5db7ca90075dcb8e21
Publikováno v:
BMC Medical Imaging, Vol 21, Iss 1, Pp 1-13 (2021)
Abstract Background Deep neural networks (DNNs) are widely investigated in medical image classification to achieve automated support for clinical diagnosis. It is necessary to evaluate the robustness of medical DNN tasks against adversarial attacks,
Externí odkaz:
https://doaj.org/article/9539814e85444e3b8817438d1bbe96a9
Autor:
Katsumi Chiyomaru, Kazuhiro Takemoto
Publikováno v:
Journal of Physics: Complexity, Vol 4, Iss 2, p 025009 (2023)
Voter model dynamics in complex networks are vulnerable to adversarial attacks. In particular, the voting outcome can be inverted by adding extremely small perturbations that are strategically generated in social networks, even when one opinion is do
Externí odkaz:
https://doaj.org/article/47af58c1868b42baa6c280cc6a809978
Autor:
Yuki Matsuo, Kazuhiro Takemoto
Publikováno v:
Applied Sciences, Vol 12, Iss 24, p 12564 (2022)
Backdoor attacks are a serious security threat to open-source and outsourced development of computational systems based on deep neural networks (DNNs). In particular, the transferability of backdoors is remarkable; that is, they can remain effective
Externí odkaz:
https://doaj.org/article/4658bf0e9a6b4877a5082bcbe87150eb
Autor:
Hokuto Hirano, Kazuhiro Takemoto
Publikováno v:
BMC Bioinformatics, Vol 20, Iss 1, Pp 1-14 (2019)
Abstract Background Co-occurrence networks—ecological associations between sampled populations of microbial communities inferred from taxonomic composition data obtained from high-throughput sequencing techniques—are widely used in microbial ecol
Externí odkaz:
https://doaj.org/article/76a1217589944912b49ff9ab3c82d32e
Autor:
Kazuki Koga, Kazuhiro Takemoto
Publikováno v:
Algorithms, Vol 15, Iss 5, p 144 (2022)
Universal adversarial attacks, which hinder most deep neural network (DNN) tasks using only a single perturbation called universal adversarial perturbation (UAP), are a realistic security threat to the practical application of a DNN for medical imagi
Externí odkaz:
https://doaj.org/article/4ccae539b7d3428484f312beab794b9b
Autor:
Issei Ueda, Kazuhiro Takemoto, Keita Watanabe, Koichiro Sugimoto, Atsuko Ikenouchi, Shingo Kakeda, Asuka Katsuki, Reiji Yoshimura, Yukunori Korogi
Publikováno v:
PeerJ, Vol 8, p e9632 (2020)
Background Although structural correlation network (SCN) analysis is an approach to evaluate brain networks, the neurobiological interpretation of SCNs is still problematic. Brain-derived neurotrophic factor (BDNF) is well-established as a representa
Externí odkaz:
https://doaj.org/article/ad133e5d6af746a6aaa38131731d7169