Isbn: 9786209497742 - detection and classification of diseases of cassava leaves: using deep neural networks with optimization algorithms (11 resultados)

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Condición: New.

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Condición: New.

Taschenbuch. Condición: Neu. DETECTION AND CLASSIFICATION OF DISEASES OF CASSAVA LEAVES | USING DEEP NEURAL NETWORKS WITH OPTIMIZATION ALGORITHMS | Bui Hai Phong | Taschenbuch | Englisch | 2026 | LAP LAMBERT Academic Publishing | EAN 9786209497742 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.…

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 68 pp. Englisch.

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Cassava stands as a vital staple crop and the most significant source of starch globally, playing a fundamental role in ensuring food security and providing income for millions of people, particularly within developing nations. Ranked as the fifth most cultivated staple food crop in the world, cassava is distinguished by its robust adaptability to diverse soil types and harsh environmental conditions. However, both agricultural productivity and farmer livelihoods face severe threats from the proliferation of diseases, including cassava mosaic disease (CMD), cassava brown streak disease (CBSD), cassava green mottle (CGM), and cassava bacterial blight (CBB).Traditional disease diagnosis remains heavily reliant on manual visual inspections conducted by specialists-a method that is not only time-consuming and subjective but also significantly limited by the scarcity of skilled plant pathologists in many regions. In this context, the development of automated and reliable methods for identifying cassava diseases has become an urgent necessity.This book introduces advanced methodologies utilizing Deep Neural Networks integrated with optimization algorithms.…

Condición: New. Print on Demand.

Paperback. Condición: new. Paperback. Cassava stands as a vital staple crop and the most significant source of starch globally, playing a fundamental role in ensuring food security and providing income for millions of people, particularly within developing nations. Ranked as the fifth most cultivated staple food crop in the world, cassava is distinguished by its robust adaptability to diverse soil types and harsh environmental conditions. However, both agricultural productivity and farmer livelihoods face severe threats from the proliferation of diseases, including cassava mosaic disease (CMD), cassava brown streak disease (CBSD), cassava green mottle (CGM), and cassava bacterial blight (CBB).Traditional disease diagnosis remains heavily reliant on manual visual inspections conducted by specialists-a method that is not only time-consuming and subjective but also significantly limited by the scarcity of skilled plant pathologists in many regions. In this context, the development of automated and reliable methods for identifying cassava diseases has become an urgent necessity.This book introduces advanced methodologies utilizing Deep Neural Networks integrated with optimization algorithms. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Condición: New. PRINT ON DEMAND.

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Cassava stands as a vital staple crop and the most significant source of starch globally, playing a fundamental role in ensuring food security and providing income for millions of people, particularly within developing nations. Ranked as the fifth most cultivated staple food crop in the world, cassava is distinguished by its robust adaptability to diverse soil types and harsh environmental conditions. However, both agricultural productivity and farmer livelihoods face severe threats from the proliferation of diseases, including cassava mosaic disease (CMD), cassava brown streak disease (CBSD), cassava green mottle (CGM), and cassava bacterial blight (CBB).Traditional disease diagnosis remains heavily reliant on manual visual inspections conducted by specialists-a method that is not only time-consuming and subjective but also significantly limited by the scarcity of skilled plant pathologists in many regions. In this context, the development of automated and reliable methods for identifying cassava diseases has become an urgent necessity.This book introduces advanced methodologies utilizing Deep Neural Networks integrated with optimization algorithms.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 68 pp. Englisch.…