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The experimental results show that the most accurate algorithm for plant leaf disease recognition is NASNetMobile architecture using transfer learning.
In this research, we proposed a DL-based cotton leaf disease detection approach using fine-tuning Transfer Learning (TL) algorithms.
8 days ago · This paper investigates the role of deep transfer learning techniques such as EfficientNet models, Xception, ResNet models, Inception, VGG, ...
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This paper proposes a Convolutional Neural Network (CNN) model for detecting diseases in cotton plants. The model implements in proposed work utilize transfer ...
This article describes a method for detecting diseases in cotton leaves based on transfer learning. Unlike the previous works focusing on a limited number of ...
This research uses a deep transfer learning model to develop a real-time mobile application for cotton crop disease detection that can be utilized by any farmer ...
Patil et al. [5] developed a deep CNN model to detect diseases in cotton plants. Augmentation, fine tuning and image processing was performed ...
This document discusses using deep transfer learning to detect diseases in cotton plants by analyzing images of cotton leaves. Specifically, it: 1) Notes that ...
As this project will help the farmers to recognize the cotton plants which are Fresh and Diseased by simply uploading the pictures of the cotton plants on the ...
Jul 14, 2024 · Transfer learning was used along with the Mask-RCNN model to identify diseases in cotton leaves, with a 94% accuracy. NasNetlarge, VGG-19, ...