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Some useful resources for learning about e-agriculture in practice are the World Bank's e-sourcebook ICT in agriculture – connecting smallholder farmers to knowledge, networks and institutions (2011), [2] ICT uses for inclusive value chains (2013), [3] ICT uses for inclusive value chains (2013) [4] and Success stories on information and ...
Machine learning can be used to spot early-warning signs of disasters and environmental issues, possibly including natural pandemics, [344] [345] earthquakes, [346] [347] [348] landslides, [349] heavy rainfall, [350] long-term water supply vulnerability, [351] tipping-points of ecosystem collapse, [352] cyanobacterial bloom outbreaks, [353] and ...
Deep learning is a subset of machine learning that focuses on utilizing neural networks to perform tasks such as classification, regression, and representation learning. The field takes inspiration from biological neuroscience and is centered around stacking artificial neurons into layers and "training" them to process data.
Emerging digital technologies have the potential to be game-changers for traditional agricultural practices. The Food and Agriculture Organization of the United Nations has referred to this change as a revolution: "a 'digital agricultural revolution' will be the newest shift which could help ensure agriculture meets the needs of the global population into the future."
The research and projects at the UADA/UAM Geospatial Science Lab involve the development of applications for new technologies in the field of environmental information sciences, geo-intelligence (advanced geo-information science and earth observation, machine and deep learning, and big data analytics), remote sensing, sUAS/drones, land ...
Deep learning has profoundly improved the performance of programs in many important subfields of artificial intelligence, including computer vision, speech recognition, natural language processing, image classification, [113] and others. The reason that deep learning performs so well in so many applications is not known as of 2021. [114]
Agricultural technology can be products, services or applications derived from agriculture that improve various input and output processes. [ 1 ] [ 2 ] Advances in agricultural science , agronomy , and agricultural engineering have led to applied developments in agricultural technology.
Waikato Environment for Knowledge Analysis (Weka) is a collection of machine learning and data analysis free software licensed under the GNU General Public License. It was developed at the University of Waikato , New Zealand and is the companion software to the book "Data Mining: Practical Machine Learning Tools and Techniques".