| Description |
1 online resource (204 p.) |
| Contents |
Intro -- Table of Content -- Title -- BENTHAM SCIENCE PUBLISHERS LTD. -- End User License Agreement (for non-institutional, personal use) -- Usage Rules: -- Disclaimer: -- Limitation of Liability: -- General: -- FOREWORD -- PREFACE -- List of Contributors -- Enhanced Machine Learning Techniques for Pest Control and Leaf Disease Identification -- Abstract -- INTRODUCTION -- RELATED WORK -- BACKGROUND STUDY -- Artificial Neural Network (ANN) -- Mayfly Optimization -- Male Mayflie's Movement -- Female Mayflie's Movement -- Mating of Mayfly -- BLACK WINDOW OPTIMIZATION -- Mathematical Evaluation |
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PROPOSED METHODOLOGY -- Pre-processing -- Leaf Image from Plants -- Segmentation Model Using Improved Canny Algorithm -- Steps of Improved Canny Algorithm -- Leaf Image Feature Selection Using Hybrid Black Widow Optimization Algorithm with Mayfly Optimization Algorithm (BWO-MA) -- Pseudo-Code of the Hybrid (BWO-MA) Algorithm -- Output: Objective Function's -RMSE -- Leaf Image Classification Using (BWO-MA) with ANN -- Hyper-Parameter Tuning With (BWO-MA) -- RESULT AND DISCUSSION -- Dataset Description -- Evaluation & Results -- CONCLUSION -- REFERENCES |
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Automatic Recognition and Classification of Tomato Leaf Diseases Using Transfer Learning Model -- Abstract -- INTRODUCTION -- EXISTING WORKS -- MATERIALS AND METHODS -- Related Works -- Convolution Neural Network -- Convolution Layer -- Activation Layer -- Pooling Layer -- Fully Connected Layer -- SqueezeNet -- PROPOSED WORK -- Image Acquisition (Dataset) -- Image Pre-Processing -- Establishing a New Deep Network Using Transfer Learning -- Recognition and Classification -- EXPERIMENTAL RESULTS AND DISCUSSION -- Experimental Setting and Environment -- Evaluation Metrics |
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Experiment Deployment and Result Analysis -- Comparison with Earlier Works -- CONCLUSION AND FUTURE SCOPE -- ACKNOWLEDGEMENTS -- REFERENCES -- Detection and Categorization of Diseases in Pearl Millet Leaves using Novel Convolutional Neural Network Model -- Abstract -- INTRODUCTION -- LITERATURE STUDY AND RELATED WORK -- DATA AND METHODOLOGY -- Data Acquisition -- Data Pre-processing -- Model Building and Validation -- Evaluation Metrics -- RESULTS AND ANALYSIS -- CONCLUSION AND DISCUSSION -- ACKNOWLEDGEMENTS -- References |
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Artificial Intelligence-based Solar Powered Robot to Identify Weed and Damage in Vegetables -- Abstract -- INTRODUCTION -- DIGITAL AGRICULTURE: IMPACT & CHALLENGES -- INTRODUCTION TO ROBOTICS -- Robotics -- Need of Robotics -- Industrial Robots -- Automation and Robotics -- Control Systems for Robotics -- Limited Sequence Robots (Non-Servo) -- Point to Point Motion -- Continuous Path Motion -- Intelligent Robots -- Presence of Movement for Robots in the Agriculture Sector -- AN INTRODUCTION TO SOLAR ENERGY -- Photovoltaic Effect on Solar Generation -- Solar Cell: Construction and Working |
| Summary |
Artificial Intelligence is vital to the evolution of agriculture into a smart industry. The objective of this book is to inform readers about how artificial intelligence is improving agriculture by exploring its applications. The book addresses several aspects of artificial intelligence applications in smart agriculture including, pest control, disease identification, weed detection, and security. Chapters are contributed by experts in agriculture, computer sc |
| Notes |
Description based upon print version of record |
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LOAD CALCULATION OF SOLAR PANELS |
| Form |
Electronic book
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| Author |
Bera, Tushar Kanti
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| ISBN |
9789815124729 |
|
9815124722 |
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