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Development And Simulation Of Ios App To Detect Cotton Plant Diseases Using Machine Learning Techniques

https://doi.org/10.2139/ssrn.4007166
0 signed · 9 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.

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What this work says

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

inferredcites →https://doi.org/10.1007/978-981-16-2354-7_24openalex-extracted
A Study of iOS Machine Learning and Artificial Intelligence Frameworks and Libraries for Cotton Plant Disease Detection
inferredcites →https://doi.org/10.1109/comitcon.2019.8862452openalex-extracted
Machine Learning based Image Processing Techniques for Satellite Image Analysis -A Survey
inferredcites →https://doi.org/10.1109/ecice47484.2019.8942690openalex-extracted
Sugarcane Disease Recognition using Deep Learning
inferredcites →https://doi.org/10.1109/hnicem.2018.8666365openalex-extracted
Mobile Platform Implementation of Lightweight Neural Network Model for Plant Disease Detection and Recognition
inferredcites →https://doi.org/10.1109/icaccs.2019.8728382openalex-extracted
Agriculture Analysis Using Data Mining And Machine Learning Techniques
inferredcites →https://doi.org/10.1109/iccids.2019.8862084openalex-extracted
Grape Leaf Disease Identification using Machine Learning Techniques
inferredcites →https://doi.org/10.1109/incit.2019.8912053openalex-extracted
iDahon: An Android Based Terrestrial Plant Disease Detection Mobile Application Through Digital Image Processing Using Deep Learning Neural Network Algorithm
inferredcites →https://doi.org/10.1109/smc.2018.00626openalex-extracted
Development of Classification System of Rice Disease Using Artificial Intelligence

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1016/j.eswa.2022.118989openalex-snapshot
An optimal hybrid multiclass SVM for plant leaf disease detection using spatial Fuzzy C-Means model
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