On the public citation graph

Development of a Recommendation System for Plant Disease Detection Using Ai

0 signed · 6 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.

Claim with ORCID

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 See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.

See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1016/j.biosystemseng.2016.08.024openalex-extracted

Plant species classification using deep convolutional neural network

inferredcites →https://doi.org/10.1016/j.compag.2020.105220openalex-extracted

New perspectives on plant disease characterization based on deep learning

inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-extracted

Deep Residual Learning for Image Recognition

inferredcites →https://doi.org/10.1109/tip.2019.2959254openalex-extracted

A Two-Stage Approach to Few-Shot Learning for Image Recognition

inferredcites →https://doi.org/10.3389/fpls.2016.01419openalex-extracted

Using Deep Learning for Image-Based Plant Disease Detection

inferredcites →https://doi.org/10.3390/plants8110468openalex-extracted

Plant Disease Detection and Classification by Deep Learning

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.