소장자료
LDR | 04372cam a2200000 a | ||
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005 | 20211103172604▲ | ||
007 | ta ▲ | ||
008 | 200811s2021 uk a 000 0 eng c▲ | ||
010 | ▼a 2020036553▲ | ||
020 | ▼a9780367535803 (hbk.)▲ | ||
020 | ▼z9781003138884 (ebk.)▲ | ||
035 | ▼a(KERIS)REF000019372970▲ | ||
040 | ▼aDLC▼beng▼cDLC▼d221016▲ | ||
050 | 0 | 0 | ▼aS494.5.D3▼bS623 2021▲ |
082 | 0 | 4 | ▼a338.10285▼223▲ |
090 | ▼a338.1▼bS636p▲ | ||
245 | 0 | 0 | ▼aSmart agriculture :▼bemerging pedagogies of deep learning, machine learning and Internet of Things /▼cedited by Govind Singh Patel ... [et.al.].▲ |
260 | ▼aLondon :▼bCRC Press/Balkema/Taylor & Francis Group,▼c[2021]▲ | ||
300 | ▼a211 p. :▼bill. ;▼c26 cm.▲ | ||
505 | 0 | ▼aMachine learning and deep learning in agriculture / Sumit Koul -- Descriptive and predictive analytics of agricultural data using machine learning algorithms / Mrs. R. Suguna, Dr. R. Uma Rani -- Discrimination between weed and crop via image analysis using machine learning algorithm / P Amsin, Dr. R. Ma Rani -- Bio-inspired optimization algorithms for machine learning in agriculture applications / P.R. MahiDar-- Agricultural modernization with forecasting stages and machine learning / A.K. Awasthi and Arun Kumar Garov--Classification of segmented image using increased global contrast for paddy plant disease / Md Abdul Muqueem, G. Raju and Govind Singh Patel -- IoT in agriculture : Survey on technology, challenges and future scope / Seema Nayak -- Role of IoT in sustainable farming / Rajasekhar Manda and P.Rajesh Kumar -- Smart farming : Crop models and decision support systems using IoT / Kanwaljeet Singh and Amandeep Kaur -- Smart irrigation in farming using internet of things / Devesh Kumar Srivastava and Priyanka Nair -- Automation systems in agriculture via IoT / Shylaja Vinay Kumar Karatangi, Reshu Agarwal and Manisha Pant -- A complete automated solution for farm field and garden nurturing using Internet of Things / S. Siva Kumar, A. M. Senthil Kumar, T. Rajesh Kumar, N. Sree Ram, V. Krishna Reddy and P. Sivakumar -- Machine intelligence techniques for agricultural production : Case study with tomato leaf disease detection / Mihir Narayan Mohanty -- Clock signal and its attribute for agriculture / Abhishek Kumar.▲ | |
520 | ▼a"This book endeavours to highlight the untapped potential of Smart Agriculture for the innovation and expansion of the agriculture sector. The sector shall make incremental progress as it learns from associations between data over time through Artificial Intelligence, deep learning and Internet of Things applications. The farming industry and smart agriculture develop from the stringent limits imposed by a farm's location, which in turn has a series of related effects with respect to supply chain management, food availability, biodiversity, farmers' decision-making and insurance, and environmental concerns among others. All of the above-mentioned aspects will derive substantial benefits from the implementation of a data-driven approach under the condition that the systems, tools and techniques to be used have been designed to handle the volume and variety of the data to be gathered. Contributions to this book have been solicited with the goal of uncovering the possibilities of engaging agriculture with equipped and effective profound learning algorithms. Most agricultural research centres are already adopting Internet of Things for the monitoring of a wide range of farm services, and there are significant opportunities for agriculture administration through the effective implementation of Machine Learning, Deep Learning, Big Data and IoT structures"-- Provided by publisher.▲ | ||
650 | 0 | ▼aArtificial intelligence▼xAgricultural applications.▲ | |
650 | 0 | ▼aAgricultural innovations.▲ | |
650 | 0 | ▼aMachine learning.▲ | |
650 | 0 | ▼aInternet of things.▲ | |
650 | 0 | ▼aBig data.▲ | |
700 | 1 | ▼aPatel, Govind Singh.▲ | |
700 | 1 | ▼aRai, Amrita.▲ | |
700 | 1 | ▼aDas, Nripendra Narayan.▲ | |
700 | 1 | ▼aSingh, R.P.▲ |
Smart agriculture :emerging pedagogies of deep learning, machine learning and Internet of Things
자료유형
국외단행본
서명/책임사항
Smart agriculture : emerging pedagogies of deep learning, machine learning and Internet of Things / edited by Govind Singh Patel ... [et.al.].
발행사항
London : CRC Press/Balkema/Taylor & Francis Group , [2021]
형태사항
211 p. : ill. ; 26 cm.
내용주기
Machine learning and deep learning in agriculture / Sumit Koul -- Descriptive and predictive analytics of agricultural data using machine learning algorithms / Mrs. R. Suguna, Dr. R. Uma Rani -- Discrimination between weed and crop via image analysis using machine learning algorithm / P Amsin, Dr. R. Ma Rani -- Bio-inspired optimization algorithms for machine learning in agriculture applications / P.R. MahiDar-- Agricultural modernization with forecasting stages and machine learning / A.K. Awasthi and Arun Kumar Garov--Classification of segmented image using increased global contrast for paddy plant disease / Md Abdul Muqueem, G. Raju and Govind Singh Patel -- IoT in agriculture : Survey on technology, challenges and future scope / Seema Nayak -- Role of IoT in sustainable farming / Rajasekhar Manda and P.Rajesh Kumar -- Smart farming : Crop models and decision support systems using IoT / Kanwaljeet Singh and Amandeep Kaur -- Smart irrigation in farming using internet of things / Devesh Kumar Srivastava and Priyanka Nair -- Automation systems in agriculture via IoT / Shylaja Vinay Kumar Karatangi, Reshu Agarwal and Manisha Pant -- A complete automated solution for farm field and garden nurturing using Internet of Things / S. Siva Kumar, A. M. Senthil Kumar, T. Rajesh Kumar, N. Sree Ram, V. Krishna Reddy and P. Sivakumar -- Machine intelligence techniques for agricultural production : Case study with tomato leaf disease detection / Mihir Narayan Mohanty -- Clock signal and its attribute for agriculture / Abhishek Kumar.
요약주기
"This book endeavours to highlight the untapped potential of Smart Agriculture for the innovation and expansion of the agriculture sector. The sector shall make incremental progress as it learns from associations between data over time through Artificial Intelligence, deep learning and Internet of Things applications. The farming industry and smart agriculture develop from the stringent limits imposed by a farm's location, which in turn has a series of related effects with respect to supply chain management, food availability, biodiversity, farmers' decision-making and insurance, and environmental concerns among others. All of the above-mentioned aspects will derive substantial benefits from the implementation of a data-driven approach under the condition that the systems, tools and techniques to be used have been designed to handle the volume and variety of the data to be gathered. Contributions to this book have been solicited with the goal of uncovering the possibilities of engaging agriculture with equipped and effective profound learning algorithms. Most agricultural research centres are already adopting Internet of Things for the monitoring of a wide range of farm services, and there are significant opportunities for agriculture administration through the effective implementation of Machine Learning, Deep Learning, Big Data and IoT structures"-- Provided by publisher.
주제
ISBN
9780367535803 (hbk.)
청구기호
338.1 S636p
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