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Comparing inception V3, VGG 16, VGG 19, CNN, and ResNet 50: A case study on early detection of a rice disease
Rice production has faced numerous challenges in recent years, and traditional methods
are still being used to detect rice diseases. This research project developed an automated …
are still being used to detect rice diseases. This research project developed an automated …
Deep learning based multi-classification model for rice disease detection
To recognise and categorise images of rice diseases, a A convolutional neural network
(CNN) model built on deep learning (DL) has been developed. The model is developed for …
(CNN) model built on deep learning (DL) has been developed. The model is developed for …
A deep learning-based model for biotic rice leaf disease detection
The detection of rice leaf disease is an essential step for implementing precise and timely
interventions, thereby mitigating the spread and minimizing the ecological and economic …
interventions, thereby mitigating the spread and minimizing the ecological and economic …
Machine learning based evaluations of stress, depression, and anxiety
One of the most severe issues in modern mental health care is depression, which affects
people of all ages and sexes equally. Nowadays, people do not have to work as hard …
people of all ages and sexes equally. Nowadays, people do not have to work as hard …
Diabetes prediction using different machine learning techniques
Even though diabetes is a worldwide epidemic, there is no cure for it. Furthermore,
Healthcare for people with diabetes costs a lot of money every year. As a result, the most …
Healthcare for people with diabetes costs a lot of money every year. As a result, the most …
Application of deep learning for detecting rice leaf diseases in jhum cultivation
Rice leaf disease poses a significant challenge to Jhum cultivation, making early and
accurate detection vital for effective disease management. This study examines two cutting …
accurate detection vital for effective disease management. This study examines two cutting …
Bean Leaf Lesions Image Classification: A Robust Ensemble Deep Learning Approach
Growing beans is important since they are a staple meal for so many people throughout the
world. Bean rust and angular leaf spot are just two of the many diseases that threaten the …
world. Bean rust and angular leaf spot are just two of the many diseases that threaten the …
A Privacy-Preserving Collaborative Federated Learning Framework for Detecting Retinal Diseases
The rapid advancement in technology has simplified human life and provides convenience.
However, this convenience has led to many lifestyle diseases like diabetes and obesity. The …
However, this convenience has led to many lifestyle diseases like diabetes and obesity. The …
[PDF][PDF] Detection of rice plant disease from RGB and grayscale images using an LW17 deep learning model.
Rice is grown almost everywhere in the world, especially in Asian countries, because it is
part of the diets of about half of the world's population. However, farmers and planting …
part of the diets of about half of the world's population. However, farmers and planting …
HECNNet: Hybrid Ensemble Convolutional Neural Network Model with Multi-Backbone Feature Extractors for Soybean Disease Classification
The purpose of this study is to classify soybean plant diseases using a new method called
Hybrid Ensemble Convolutional Neural Networks (HECNNet). To effectively extract unique …
Hybrid Ensemble Convolutional Neural Networks (HECNNet). To effectively extract unique …