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1. |
Record Nr. |
UNINA9910736024803321 |
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Autore |
Bansal Jagdish Chand |
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Titolo |
Computer Vision and Machine Learning in Agriculture, Volume 3 / / edited by Jagdish Chand Bansal, Mohammad Shorif Uddin |
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Pubbl/distr/stampa |
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Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 |
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ISBN |
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Edizione |
[1st ed. 2023.] |
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Descrizione fisica |
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1 online resource (215 pages) |
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Collana |
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Algorithms for Intelligent Systems, , 2524-7573 |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Computational intelligence |
Machine learning |
Robotics |
Agriculture |
Image processing - Digital techniques |
Computer vision |
Computational Intelligence |
Machine Learning |
Computer Imaging, Vision, Pattern Recognition and Graphics |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Leveraging Computer Vision for Precision Viticulture -- An intelligent vision-guided framework of the unmanned aerial system for precision agriculture -- Data Preprocessing Techniques for Supervised Learning on Agricultural Data -- Strawberries Maturity Level Detection Using Convolutional Neural Network (CNN) and Ensemble Method -- Recognition of Fresh and Rotten Fruits through the Development of a Dataset. |
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Sommario/riassunto |
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This book is as an extension of the previous two volumes on “Computer Vision and Machine Learning in Agriculture”. This volume 3 discusses solutions to the problems of agricultural production by rendering advanced machine learning including deep learning tools and techniques. The book contains 13 chapters that focus on in-depth research outputs in precision agriculture, crop farming, horticulture, floriculture, vertical farming, animal husbandry, disease detection, |
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plant recognition, production yield, product quality, defect assessment, and overall automation through robots and drones. The topics covered in the current volume, along with the previous volumes, are comprehensive literature for both beginners and experienced in this domain. |
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