Review of: "Enhancing Cocoa Crop Resilience in Ghana: The Application of Convolutional Neural Networks for Early Detection of Disease and Pest Infestations"
Year: 2024
Type: peer-review
Abstract: Potential competing interests: No potential competing interests to declare.The authors suggest a CNN model for the detection of cocoa diseases.The paper is grammatically well written.The abstract is very vague; please focus on the motivation, method, and results.After reading the introduction, the reader still doesn't know about the specific approach used in the study or the results obtained.If announced there, they can provide a better insight into the content of the research.The literature review should specifically mention accuracies reached by existing plant disease detection models.The document contains no information about the architecture of the CNN used to train the model nor the accuracy obtained after training, so it's hard to evaluate the study.
Source: Qeios
DOI: 10.32388/kkaen5
Author: Emmanuel Moupojou
Institution: Université de Technologie de Troyes
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: diamond
OpenAlex ID: W4391735596
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