On the public citation graph
Revolutionizing Plant Pathogen Conservation: The Past, Present, and Future of AI in Preserving Natural Ecosystems
0 signed · 10 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1016/j.compag.2020.105220zenodo-depositor-declared
New perspectives on plant disease characterization based on deep learning
inferredcites →https://doi.org/10.1016/j.compag.2022.107119zenodo-depositor-declared
Towards leveraging the role of machine learning and artificial intelligence in precision agriculture and smart farming
inferredcites →https://doi.org/10.1016/j.ecolmodel.2022.110167zenodo-depositor-declared
Farm monitoring and disease prediction by classification based on deep learning architectures in sustainable agriculture
inferredcites →https://doi.org/10.1016/j.future.2021.08.006zenodo-depositor-declared
Recent advancements and challenges of Internet of Things in smart agriculture: A survey
inferredcites →https://doi.org/10.1046/j.1365-3059.1999.00361.xzenodo-depositor-declared
Biodiversity, plant pathogens and conservation
inferredcites →https://doi.org/10.1109/icip49359.2023.10222401zenodo-depositor-declared
Pairwise Feature Learning for Unseen Plant Disease Recognition
inferredcites →https://doi.org/10.1111/ppa.13448zenodo-depositor-declared
A case for conserving plant pathogens
inferredcites →https://doi.org/10.3389/fpls.2016.01419zenodo-depositor-declared
Using Deep Learning for Image-Based Plant Disease Detection
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1079/9781800628649.0001openalex-snapshot
Artificial Intelligence: An Introduction to Technical Advancements and Current Biological Applications in Plants
inferred← citeshttps://doi.org/10.1145/3746027.3758192openalex-snapshot
Deep-Plant-Disease Dataset Is All You Need for Plant Disease Identification
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.