Automatic Detection of Tomato Diseases using Fine-tuned pre-trained Deep Learning Models

Author:

Pradhan Priyanka1,Kumar Brajesh2

Affiliation:

1. MJP Rohilkhand University,Department of Computer Science & IT,Bareilly,India,243006

2. MJP Rohilkhand University,Atal Center for Artificial Intelligence,Bareilly,India,243006

Publisher

IEEE

Reference21 articles.

1. Rethinking the inception architecture for computer vision;szegedy;Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition,2013

2. Deep inside convolutional networks: Visualising image classification models and saliency maps;simonyan,2013

3. MobileNetV2: Inverted Residuals and Linear Bottlenecks

4. Xception: Deep learning with depthwise separable convolutions;chollet;Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition,2017

5. Performance of deep learning vs machine learning in plant leaf disease detection

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1. Tomato Guard: A Predictive Model for Disease Prediction and Treatment Recommendation in Tomato Plants;2024 3rd International Conference on Applied Artificial Intelligence and Computing (ICAAIC);2024-06-05

2. Plant disease detection using leaf images and an involutional neural network;Environment Conservation Journal;2024-04-30

3. Multiclassification of Tomato Diseases: CNN and Random Forest Hybrid Approach;2024 International Conference on Automation and Computation (AUTOCOM);2024-03-14

4. Transfer Learning-Based Tomato Disease Prediction using Leaf Images;2023 International Conference on Recent Advances in Science and Engineering Technology (ICRASET);2023-11-23

5. A Comprehensive Review on Deep Learning and Machine Learning Approaches for Tomato Leaf Disease Identification;2023 8th International Conference on Communication and Electronics Systems (ICCES);2023-06-01

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