Zobrazeno 1 - 10
of 599
pro vyhledávání: '"interactive machine learning"'
Publikováno v:
Ecotoxicology and Environmental Safety, Vol 289, Iss , Pp 117482- (2025)
The manual counting of juveniles in enchytraeid soil toxicity tests is time-consuming, labour-intensive, repetitive, prone to subjectivity, but can potentially be automated through deep learning methods using convolutional neural networks. This study
Externí odkaz:
https://doaj.org/article/651342764f45455cbd50db39b2ac41da
Autor:
Andreas Trojan, Emanuele Laurenzi, Stephan Jüngling, Sven Roth, Michael Kiessling, Ziad Atassi, Yannick Kadvany, Meinrad Mannhart, Christian Jackisch, Gerd Kullak-Ublick, Hans Friedrich Witschel
Publikováno v:
Frontiers in Digital Health, Vol 6 (2024)
BackgroundThe use of smartphone apps in cancer patients undergoing systemic treatment can promote the early detection of symptoms and therapy side effects and may be supported by machine learning (ML) for timely adaptation of therapies and reduction
Externí odkaz:
https://doaj.org/article/b73687fc63bc423ea85ada7bc1ad7170
Publikováno v:
IEEE Access, Vol 12, Pp 162191-162203 (2024)
Recent progress in image generation has made it possible to create high-quality images. Techniques using diffusion models have shown great potential in producing high-quality images from simple prompts, attracting inexperienced beginners in deep lear
Externí odkaz:
https://doaj.org/article/56b669bdd5c94661bafcda123ded20f7
Autor:
H. Poppy Clark, Abraham George Smith, Daniel McKay Fletcher, Ann I. Larsson, Marcel Jaspars, Laurence H. De Clippele
Publikováno v:
Royal Society Open Science, Vol 11, Iss 5 (2024)
Advancing imaging technologies are drastically increasing the rate of marine video and image data collection. Often these datasets are not analysed to their full potential as extracting information for multiple species is incredibly time-consuming. T
Externí odkaz:
https://doaj.org/article/f36a037448b94fdba06551f99d73919d
Publikováno v:
Machine Learning and Knowledge Extraction, Vol 5, Iss 4, Pp 1519-1538 (2023)
The rise of machine-learning applications in domains with critical end-user impact has led to a growing concern about the fairness of learned models, with the goal of avoiding biases that negatively impact specific demographic groups. Most existing b
Externí odkaz:
https://doaj.org/article/018e7c40286944bd89ca20b50af98b43
Publikováno v:
Smart Agricultural Technology, Vol 5, Iss , Pp 100254- (2023)
In visions of the future of agriculture, it is predicted that Artificial Intelligence and Robotics will revolutionize farming. Artificial Intelligence (AI) is not always clearly visible to the end users, who are in this case farmers. AI methods are u
Externí odkaz:
https://doaj.org/article/cb4b9f0a074d40ab9754a3be862ce9a7
Publikováno v:
Machine Learning and Knowledge Extraction, Vol 4, Iss 4, Pp 994-1010 (2022)
Interactive Machine Learning (IML) can enable intelligent systems to interactively learn from their end-users, and is quickly becoming more and more relevant to many application domains. Although it places the human in the loop, interactions are most
Externí odkaz:
https://doaj.org/article/e74222e2ec6a4e6bb47dba82ec424428
Akademický článek
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Akademický článek
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Publikováno v:
Entropy, Vol 25, Iss 10, p 1443 (2023)
Though an accurate measurement of entropy, or more generally uncertainty, is critical to the success of human–machine teams, the evaluation of the accuracy of such metrics as a probability of machine correctness is often aggregated and not assessed
Externí odkaz:
https://doaj.org/article/2a1de2eab7ac461e9e6785079f02248e