Plant Disease Detection Using (37 results)

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Taschenbuch. Condition: Neu. KrishiMitra : Hybrid Approach for Plant Disease Detection | A Hybrid Deep Learning Approach Using CNN, Transformer, and Attention Mechanism for Smart Agriculture | Atharv Khawle (u. a.) | Taschenbuch | Englisch | 2026 | LAP LAMBERT Academic Publishing | EAN 9786209919732 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.…

Taschenbuch. Condition: Neu. Detection of Bud Blight Disease caused by GBNV | Groundnut Bud Necrosis Virus (GBNV) on Tomato Plant using Image Processing Algorithm | Kaveri Umesh Kadam | Taschenbuch | Englisch | 2021 | LAP LAMBERT Academic Publishing | EAN 9786203927535 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.…

Paperback. Condition: new. Paperback. AI-Based Plant Disease Detection Using Deep Convolutional Neural Networks presents a focused technical treatment of computer vision and deep learning methods for identifying plant diseases from leaf images. The book explains how image-based analysis can support automated disease recognition by combining visual feature extraction, convolutional neural networks, image classification, and machine learning principles. It introduces the role of digital plant imagery in agricultural diagnostics and describes how deep neural architectures learn discriminative patterns associated with visible symptoms such as lesions, discoloration, spots, and other disease-related changes.The book provides a structured view of the computational pipeline used in AI-based plant disease detection, from image acquisition and preparation through feature learning, model training, classification, and evaluation. Particular attention is given to deep convolutional neural networks because they can learn hierarchical image representations directly from visual data, reducing dependence on manually engineered features. The discussion places these methods within the broader context of precision agriculture, smart farming, crop monitoring, and agricultural information systems. A technical guide to deep convolutional neural networks for automated plant disease detection, image classification, and agricultural decision support systems. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

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Condition: New. Prof. (Dr.) Nebojsa Bacanin obtained a PhD in 2015 from the Faculty of Mathematics, University of Belgrade, Serbia (in Computer Science, average grade 10,00). He started his university career in Serbia 18 years ago at the Graduate School of Comput.

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PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In agriculture field there are various diseases; especially leaf diseases are the most popular diseases where spots occurs on the leaves. If these spots are not detected on time it may causes several losses. Insects are also affecting the leaves, if not treated on time may cause severe loss. Excessive use of pesticides for plant treatment increases the cost and environmental pollution so their use must be minimized. It is observed that many farmers are still using traditional methods for spraying fertilizers. These methods are more time and money consuming and also require large man power. By using traditional methods for spraying fertilizers may cause different effects on farmer¿s health and it does not give accurate results. The solution for the discussed problem is to design autonomous robot for performing different farming work like detect the diseases on crop, suggest the pesticide for that disease and spray the fertilizer on crop. By using autonomous farming robot save the excessive use of pesticide, save labour cost and protect farmer¿s health from pesticide. 76 pp. Englisch.…

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The book reviews the concept of various digital image processing techniques used for the detection of plant diseases. Disease detection involves steps like image acquisition, image pre-processing, image segmentation, feature extraction, and classification. Feature extraction brief about Texture features, Color features, Shape features and in classification section it discusses the following classifiers like Artificial Neural Networks, Back Propagation Neural Network, Support Vector Machine, Fuzzy Classifier, Color analysis, K-Nearest Neighbor. 56 pp. Englisch.…

Paperback. Condition: new. Paperback. AI-Based Plant Disease Detection Using Deep Convolutional Neural Networks presents a focused technical treatment of computer vision and deep learning methods for identifying plant diseases from leaf images. The book explains how image-based analysis can support automated disease recognition by combining visual feature extraction, convolutional neural networks, image classification, and machine learning principles. It introduces the role of digital plant imagery in agricultural diagnostics and describes how deep neural architectures learn discriminative patterns associated with visible symptoms such as lesions, discoloration, spots, and other disease-related changes.The book provides a structured view of the computational pipeline used in AI-based plant disease detection, from image acquisition and preparation through feature learning, model training, classification, and evaluation. Particular attention is given to deep convolutional neural networks because they can learn hierarchical image representations directly from visual data, reducing dependence on manually engineered features. The discussion places these methods within the broader context of precision agriculture, smart farming, crop monitoring, and agricultural information systems. A technical guide to deep convolutional neural networks for automated plant disease detection, image classification, and agricultural decision support systems. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

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Paperback. Condition: new. Paperback. AI-Based Plant Disease Detection Using Deep Convolutional Neural Networks presents a focused technical treatment of computer vision and deep learning methods for identifying plant diseases from leaf images. The book explains how image-based analysis can support automated disease recognition by combining visual feature extraction, convolutional neural networks, image classification, and machine learning principles. It introduces the role of digital plant imagery in agricultural diagnostics and describes how deep neural architectures learn discriminative patterns associated with visible symptoms such as lesions, discoloration, spots, and other disease-related changes.The book provides a structured view of the computational pipeline used in AI-based plant disease detection, from image acquisition and preparation through feature learning, model training, classification, and evaluation. Particular attention is given to deep convolutional neural networks because they can learn hierarchical image representations directly from visual data, reducing dependence on manually engineered features. The discussion places these methods within the broader context of precision agriculture, smart farming, crop monitoring, and agricultural information systems. A technical guide to deep convolutional neural networks for automated plant disease detection, image classification, and agricultural decision support systems. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - AI-Based Plant Disease Detection Using Deep Convolutional Neural Networks presents a focused technical treatment of computer vision and deep learning methods for identifying plant diseases from leaf images. The book explains how image-based analysis can support automated disease recognition by combining visual feature extraction, convolutional neural networks, image classification, and machine learning principles. It introduces the role of digital plant imagery in agricultural diagnostics and describes how deep neural architectures learn discriminative patterns associated with visible symptoms such as lesions, discoloration, spots, and other disease-related changes.The book provides a structured view of the computational pipeline used in AI-based plant disease detection, from image acquisition and preparation through feature learning, model training, classification, and evaluation. Particular attention is given to deep convolutional neural networks because they can learn hierarchical image representations directly from visual data, reducing dependence on manually engineered features. The discussion places these methods within the broader context of precision agriculture, smart farming, crop monitoring, and agricultural information systems. …

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In agriculture field there are various diseases; especially leaf diseases are the most popular diseases where spots occurs on the leaves. If these spots are not detected on time it may causes several losses. Insects are also affecting the leaves, if not treated on time may cause severe loss. Excessive use of pesticides for plant treatment increases the cost and environmental pollution so their use must be minimized. It is observed that many farmers are still using traditional methods for spraying fertilizers. These methods are more time and money consuming and also require large man power. By using traditional methods for spraying fertilizers may cause different effects on farmer's health and it does not give accurate results. The solution for the discussed problem is to design autonomous robot for performing different farming work like detect the diseases on crop, suggest the pesticide for that disease and spray the fertilizer on crop. By using autonomous farming robot save the excessive use of pesticide, save labour cost and protect farmer's health from pesticide. …

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Bhong VijayMr.Vijay Suresh Bhong received B.E. E&TC from Solapur University,Solapur in 2014. M.E.(VLSI & Embedded System) from Savitribai Phule Pune University Pune in 2016 respectively. Currently Working as Assistant Professor in SV.…

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The book reviews the concept of various digital image processing techniques used for the detection of plant diseases. Disease detection involves steps like image acquisition, image pre-processing, image segmentation, feature extraction, and classification. Feature extraction brief about Texture features, Color features, Shape features and in classification section it discusses the following classifiers like Artificial Neural Networks, Back Propagation Neural Network, Support Vector Machine, Fuzzy Classifier, Color analysis, K-Nearest Neighbor.…

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Shifani S. AgnesS. Agnes Shifani is currently working as an Assistant Professor in the Department of Electronics and Communication Engineering, Jeppiaar Maamallan Engineering College, Chennai. She has 9 years of teaching experience a.…

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Plant diseases continue to be a significant challenge in modern agriculture, often resulting in decreased crop productivity and economic loss. This book introduces a hybrid deep learning approach for accurate and efficient plant disease detection by combining CNN, Transformer, and Attention Mechanism. The proposed system is designed to capture both detailed local features and broader global patterns, enabling reliable performance even under real-world conditions.Developed as a practical and scalable solution, the system integrates modern frameworks such as TensorFlow and Django, along with efficient data processing techniques. It provides valuable insights into intelligent agricultural systems that support early disease identification, enhance decision-making, and promote sustainable farming practices.…

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In agriculture field there are various diseases; especially leaf diseases are the most popular diseases where spots occurs on the leaves. If these spots are not detected on time it may causes several losses. Insects are also affecting the leaves, if not treated on time may cause severe loss. Excessive use of pesticides for plant treatment increases the cost and environmental pollution so their use must be minimized. It is observed that many farmers are still using traditional methods for spraying fertilizers. These methods are more time and money consuming and also require large man power. By using traditional methods for spraying fertilizers may cause different effects on farmer's health and it does not give accurate results. The solution for the discussed problem is to design autonomous robot for performing different farming work like detect the diseases on crop, suggest the pesticide for that disease and spray the fertilizer on crop. By using autonomous farming robot save the excessive use of pesticide, save labour cost and protect farmer's health from pesticide.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 76 pp. Englisch.…

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The book reviews the concept of various digital image processing techniques used for the detection of plant diseases. Disease detection involves steps like image acquisition, image pre-processing, image segmentation, feature extraction, and classification. Feature extraction brief about Texture features, Color features, Shape features and in classification section it discusses the following classifiers like Artificial Neural Networks, Back Propagation Neural Network, Support Vector Machine, Fuzzy Classifier, Color analysis, K-Nearest Neighbor.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 56 pp. Englisch.…

Taschenbuch. Condition: Neu. AI-Based Plant Disease Detection Using Deep Convolutional Neural Networks | Nancy Kova | Taschenbuch | Englisch | 2026 | SHARK NAIL | EAN 9781962116602 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. …