Results 181 to 190 of about 1,552,062 (375)

Recent Advancements in Topic Modeling Techniques for Healthcare, Bioinformatics, and Other Potential Applications

open access: yesAdvanced Intelligent Systems, EarlyView.
This article offers a comprehensive review of topic modeling techniques, tracing their evolution from inception to recent developments. It explores methods such as latent Dirichlet allocation, latent semantic analysis, non‐negative matrix factorization, probabilistic latent semantic analysis, Top2Vec, and BERTopic, highlighting their strengths ...
Pratima Kumari   +6 more
wiley   +1 more source

Increasing the fungal inoculation of mine tailings from 1 to 2% decreases plant oxidative stress and increases the soil respiration rate

open access: yesScientific Reports
There is a knowledge gap about the quantitative aspects of mycorrhizal fungi’s influence on ecological succession on tailings. Here, we demonstrate that inoculating mine tailings with 2% fungi yields significantly better results in terms of plant biomass
Aurora Neagoe   +7 more
doaj   +1 more source

Accelerating Pinned Insect Specimen Digitization: A Deep Learning Pipeline for Future Collaborative Robots

open access: yesAdvanced Intelligent Systems, EarlyView.
The study presents a prototype novel workflow that utilizes artificial intelligence for the digitization of natural history collections, which would fit within a robotic‐integrated system. The work focuses on a collaborative‐robot (cobot) inspired workflow to digitize one of the largest collections housed at the Natural History Museum UK: pinned ...
Naifeng Zhang   +4 more
wiley   +1 more source

Taxonomy, biology, and clinical aspects of Fusarium species

open access: yesClinical Microbiology Reviews, 1994
P. Nelson, M. Dignani, E. Anaissie
semanticscholar   +1 more source

Computational Models of Multisensory Integration with Recurrent Neural Networks: A Critical Review and Future Directions

open access: yesAdvanced Intelligent Systems, EarlyView.
This review outlines how recurrent neural networks model multisensory integration by capturing temporal and probabilistic features of sensory input. Key developments, challenges, and future directions are summarized, providing insights into biologically inspired AI. Multisensory integration (MSI) is a core brain function underlying perception, learning,
Ehsan Bolhasani   +2 more
wiley   +1 more source

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