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Related Concept Videos

Overview of Fungi01:29

Overview of Fungi

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Fungi are a diverse group of eukaryotes more closely related to animals than other eukaryotes. Fungal cell walls comprise chitin, a polysaccharide that provides structural strength, and glucans, which contribute to flexibility and integrity. Other polysaccharides, such as mannans and galactosans, may supplement or replace chitin in some fungi. These adaptations, along with their preference for acidic environments and tolerance for high osmotic pressure, enable fungi to thrive in various...
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Fungal Phylum Basidiomycota01:26

Fungal Phylum Basidiomycota

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Basidiomycota is a diverse phylum of fungi that includes ecologically significant decomposers such as white rot fungi, symbionts like mycorrhizal fungi, plant pathogens such as rusts and smuts, and edible species like Agaricus bisporus (the common button mushroom). These fungi play crucial roles in nutrient cycling, symbiotic relationships, and even human health. Their defining feature is the basidium, a microscopic club-shaped structure responsible for producing basidiospores.Fruiting Bodies...
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Fungal Phylum Ascomycota01:28

Fungal Phylum Ascomycota

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Phylum Ascomycota, a major division within the subkingdom Dikarya, comprises a diverse range of fungal species, including both unicellular yeasts and filamentous molds such as Aspergillus and Penicillium. These fungi thrive in a variety of habitats, from aquatic ecosystems to terrestrial environments, playing crucial ecological and economic roles.Morphology and ReproductionThe defining characteristic of Ascomycetes, commonly referred to as sac fungi, is the ascus—a sac-like structure that...
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Fungal Group Zygomycota01:29

Fungal Group Zygomycota

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Zygomycota, previously classified as a distinct fungal group, are primarily terrestrial, saprophytic molds that play a crucial role as decomposers. Recent phylogenetic studies have revealed that these fungi are now divided into two major clades — Mucoromycota, which includes many symbiotic species, and Zoopagomycota, which primarily consists of parasitic and pathogenic fungi. These groups exhibit distinct ecological roles and reproductive strategies while sharing key structural and...
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Fungal Phylum Microsporidia01:28

Fungal Phylum Microsporidia

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Microsporidia are a group of obligate intracellular fungi that were initially classified as protists but were later reclassified based on phylogenetic, molecular, and structural evidence linking them to the Chytridiomycota. These unicellular, non-motile organisms are highly specialized parasites that infect a wide range of animal hosts, including humans. They have evolved extensive genomic and metabolic reductions, making them highly dependent on their hosts for survival.Morphology and Genomic...
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Automatic Fungi Recognition: Deep Learning Meets Mycology.

Lukáš Picek1, Milan Šulc2, Jiří Matas2

  • 1Department of Cybernetics, Faculty of Applied Sciences, University of West Bohemia, 30100 Pilsen, Czech Republic.

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|January 22, 2022
PubMed
Summary
This summary is machine-generated.

An AI-powered FungiVision system boosted citizen science, increasing data collection fourfold. This AI tool, achieving 93% accuracy, also enabled a new dataset for improved fungi recognition.

Keywords:
artificial intelligenceclassificationcomputer visionfine-grainedfungimachine learningrecognitionspeciesspecies recognition

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Area of Science:

  • Mycology
  • Artificial Intelligence
  • Citizen Science

Background:

  • Citizen science initiatives can significantly enhance ecological data collection.
  • Accurate species identification is crucial for biodiversity monitoring and research.
  • AI-powered tools offer potential solutions for real-time species recognition.

Purpose of the Study:

  • To develop and deploy an AI-based system (FungiVision) for real-time fungi species recognition.
  • To create a novel, fine-grained fungi classification dataset (Danish Fungi 2020) with rich metadata.
  • To improve fungi recognition accuracy using AI and citizen-collected data.

Main Methods:

  • Development of FungiVision, a mobile application with a human-in-the-loop AI for real-time fungi identification.
  • Creation of the Danish Fungi 2020 dataset, featuring species-level labels and observation metadata.
  • Implementation of a Vision Transformer architecture for fungi recognition, leveraging metadata.

Main Results:

  • FungiVision increased citizen participation in data collection by 400%.
  • The system achieved nearly 93% accuracy with human-in-the-loop validation.
  • The novel AI model, trained on the DF20 dataset, reduced recognition error by 46.75% compared to the previous system.

Conclusions:

  • AI-driven tools like FungiVision can effectively engage the public in citizen science.
  • The integration of metadata significantly enhances the accuracy of AI-based species classification.
  • A collaborative approach, with continuous data flow, fosters a virtuous cycle of improvement for both AI systems and scientific understanding.