AIMC Topic: Fungi

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Automatic Fungi Recognition: Deep Learning Meets Mycology.

Sensors (Basel, Switzerland) Jan 14, 2022
The article presents an AI-based fungi species recognition system for a citizen-science community. The system's real-time identification too - FungiVision - with a mobile application front-end, led to increased public interest in fungi, quadrupling t...
Mobile Applications Fungi Mycology Neural Networks, Computer Deep Learning Humans
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Deep learning-based quantification of arbuscular mycorrhizal fungi in plant roots.

The New phytologist Sep 16, 2021
Soil fungi establish mutualistic interactions with the roots of most vascular land plants. Arbuscular mycorrhizal (AM) fungi are among the most extensively characterised mycobionts to date. Current approaches to quantifying the extent of root colonis...
Glomeromycota Lotus Mycorrhizae Fungi Symbiosis Deep Learning Plant Roots
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The design and application of an automated microscope developed based on deep learning for fungal detection in dermatology.

Mycoses Dec 7, 2020
BACKGROUND: Light microscopy to study the infection of fungi in skin specimens is time-consuming and requires automation.
Humans Automation, Laboratory Sensitivity and Specificity Microscopy Nails Microscopy, Fluorescence Deep Learning Hair Skin Image Processing, Computer-Assisted Fungi
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Scalable classification of organisms into a taxonomy using hierarchical supervised learners.

Journal of bioinformatics and computational biology Oct 29, 2020
Accurately identifying organisms based on their partially available genetic material is an important task to explore the phylogenetic diversity in an environment. Specific fragments in the DNA sequence of a living organism have been defined as DNA ba...
DNA Barcoding, Taxonomic Classification Chiroptera Databases, Genetic Fungi Rodentia Ferns Animals Birds Deep Learning Support Vector Machine Phylogeny Algorithms
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Assigning the Origin of Microbial Natural Products by Chemical Space Map and Machine Learning.

Biomolecules Sep 28, 2020
Microbial natural products (NPs) are an important source of drugs, however, their structural diversity remains poorly understood. Here we used our recently reported MinHashed Atom Pair fingerprint with diameter of four bonds (MAP4), a fingerprint sui...
Fungi ROC Curve Databases, Chemical Bacteria Biological Products Machine Learning Area Under Curve
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Deep learning approach to describe and classify fungi microscopic images.

PloS one Jun 30, 2020
Preliminary diagnosis of fungal infections can rely on microscopic examination. However, in many cases, it does not allow unambiguous identification of the species due to their visual similarity. Therefore, it is usually necessary to use additional b...
Deep Learning Fungi Image Processing, Computer-Assisted Microscopy Support Vector Machine
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Its2vec: Fungal Species Identification Using Sequence Embedding and Random Forest Classification.

BioMed research international May 27, 2020
Fungi play essential roles in many ecological processes, and taxonomic classification is fundamental for microbial community characterization and vital for the study and preservation of fungal biodiversity. To cope with massive fungal barcode data, t...
Computational Biology Machine Learning Software DNA, Fungal Fungi DNA Barcoding, Taxonomic Algorithms
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Optimization of fungi co-fermentation for improving anthraquinone contents and antioxidant activity using artificial neural networks.

Food chemistry Jan 7, 2020
The fermentation products of edible fungi are rich in anthraquinones and have a variety of activities, including the antioxidant activity. Because of the large number of combinations, it is very difficult to obtain the optimal multi-strains co-fermen...
Neural Networks, Computer Fermentation Industrial Microbiology Antioxidants Fungi Algorithms Anthraquinones Reproducibility of Results
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A Laboratory-Built Fully Automated Ultrasonication Robot for Filamentous Fungi Homogenization.

SLAS technology Jul 30, 2019
This article presents the design and development of a new hands-free ultrasonication robot for filamentous fungi homogenization. The platform was constructed with a modified inexpensive 3D printer, equipped with an upward-facing camera, a custom-desi...
Fungi Image Processing, Computer-Assisted Sonication Spectroscopy, Fourier Transform Infrared Printing, Three-Dimensional Cell Wall Automation, Laboratory Robotics Ultrasonic Waves Mucor
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Predicting the concentration of indoor culturable fungi using a kernel-based extreme learning machine (K-ELM).

International journal of environmental health research Apr 27, 2019
Indoor fungal is of great significance for human health. The kernel-based extreme learning machine is employed to determine the most important parameters for predicting the concentration of indoor culturable fungi (ICF). For model training and statis...
Housing China Neural Networks, Computer Environmental Monitoring Air Microbiology Machine Learning Fungi
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