Rice Image Classification and Detection using improvised VGG16 Model through Deep Learning Techniques

The analysis and sorting of rice seeds have been described using a rather quick computer vision system. In recent years, rice crops have been widely acknowledged as one of the major energy sources for resource creation. In the future growth of the agricultural sector, rice plants are seen as a growi...

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Bibliographic Details
Published in2023 IEEE Renewable Energy and Sustainable E-Mobility Conference (RESEM) pp. 1 - 4
Main Authors Gupta, Rupesh, Gill, Kanwarpartap Singh
Format Conference Proceeding
LanguageEnglish
Published IEEE 17.05.2023
Subjects
Classification
Computer vision
Confusion matrix
Convolutional Neural Network
Convolutional neural networks
Deep learning
Productivity
Renewable energy sources
Rice Image Detection
Seeds (agriculture)
Sociology
VGG16 Model
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Summary:The analysis and sorting of rice seeds have been described using a rather quick computer vision system. In recent years, rice crops have been widely acknowledged as one of the major energy sources for resource creation. In the future growth of the agricultural sector, rice plants are seen as a growing reason behind the agricultural, economic, and community loss. All through these years, analysts have been fascinated by how to analyze plants utilizing picture preparing methods. Each hyperparameter must first have a range of values specified before the model is trained with those values. The VGG16 models' classification victory rates were 99.6% for accuracy prediction. The outputs show that the models utilized within the research for classifying rice assortments will be effectively used in this research work.
DOI:10.1109/RESEM57584.2023.10236020