ISBN: 9786204211114 - detection of rice hispa disease using a deep learning model: cnn model for detection of rice hispa disease severity levels (5 resultados)

Taschenbuch. Condición: Neu. Detection of Rice Hispa Disease using a Deep Learning Model | CNN model for detection of Rice Hispa Disease Severity Levels | Vinay Kukreja (u. a.) | Taschenbuch | Englisch | 2021 | LAP LAMBERT Academic Publishing | EAN 9786204211114 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. …

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Agriculture is the most important element of the globe, and large-scale agricultural operations around the world make it more susceptible to numerous diseases. Rice is one of the most important agricultural plants cultivated in enormous quantities. There are a variety of rice illnesses that impact rice crop plantations in various ways, and detecting and recognising them is one of the most difficult tasks. An endeavour has been initiated to use deep learning to recognise rice hispa illness. In order to carry out the experimental work with a real-time dataset of rice hispa and healthy rice crop plant, a CNN-based deep learning approach was used. The detection of rice hispa disease was divided into two parts: the first was a binary classification based on healthy and sick plants, and the second was a multi-classification based on five severity levels of the disease. The suggested architecture and model serves as a rice disease detection (RDD) system for rice hispa disease, assisting farmers and cultivators in recognising and detecting rice crop plants and taking appropriate and timely action. 64 pp. Englisch.…

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Agriculture is the most important element of the globe, and large-scale agricultural operations around the world make it more susceptible to numerous diseases. Rice is one of the most important agricultural plants cultivated in enormous quantities. There are a variety of rice illnesses that impact rice crop plantations in various ways, and detecting and recognising them is one of the most difficult tasks. An endeavour has been initiated to use deep learning to recognise rice hispa illness. In order to carry out the experimental work with a real-time dataset of rice hispa and healthy rice crop plant, a CNN-based deep learning approach was used. The detection of rice hispa disease was divided into two parts: the first was a binary classification based on healthy and sick plants, and the second was a multi-classification based on five severity levels of the disease. The suggested architecture and model serves as a rice disease detection (RDD) system for rice hispa disease, assisting farmers and cultivators in recognising and detecting rice crop plants and taking appropriate and timely action.…

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Kukreja VinayDr. Vinay Kukreja is presently working as an Associate Professor in Department of Computer Science and Engineering at Chitkara University, Punjab, India. His research areas are machine learning, deep learning and agile d.…

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Agriculture is the most important element of the globe, and large-scale agricultural operations around the world make it more susceptible to numerous diseases. Rice is one of the most important agricultural plants cultivated in enormous quantities. There are a variety of rice illnesses that impact rice crop plantations in various ways, and detecting and recognising them is one of the most difficult tasks. An endeavour has been initiated to use deep learning to recognise rice hispa illness. In order to carry out the experimental work with a real-time dataset of rice hispa and healthy rice crop plant, a CNN-based deep learning approach was used. The detection of rice hispa disease was divided into two parts: the first was a binary classification based on healthy and sick plants, and the second was a multi-classification based on five severity levels of the disease. The suggested architecture and model serves as a rice disease detection (RDD) system for rice hispa disease, assisting farmers and cultivators in recognising and detecting rice crop plants and taking appropriate and timely action.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 64 pp. Englisch.…