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Challenges to use machine learning in agricultural big data: a systematic literature review
Agricultural Big Data is a set of technologies that allows responding to the challenges of the
new data era. In conjunction with machine learning, farmers can use data to address …
new data era. In conjunction with machine learning, farmers can use data to address …
Machine learning with big data: Challenges and approaches
The Big Data revolution promises to transform how we live, work, and think by enabling
process optimization, empowering insight discovery and improving decision making. The …
process optimization, empowering insight discovery and improving decision making. The …
Age of information: A new concept, metric, and tool
Age of information (AoI) was introduced in the early 2010s as a notion to characterize the
freshness of the knowledge a system has about a process observed remotely. AoI was …
freshness of the knowledge a system has about a process observed remotely. AoI was …
[HTML][HTML] Face mask recognition system using CNN model
G Kaur, R Sinha, PK Tiwari, SK Yadav, P Pandey… - Neuroscience …, 2022 - Elsevier
COVID-19 epidemic has swiftly disrupted our day-to-day lives affecting the international
trade and movements. Wearing a face mask to protect one's face has become the new …
trade and movements. Wearing a face mask to protect one's face has become the new …
Role of IoT technologies in big data management systems: A review and Smart Grid case study
Abstract Empowered by Internet of Things (IoT) and cloud computing platforms, the concept
of smart cities is making a transition from conceptual models to development and …
of smart cities is making a transition from conceptual models to development and …
[HTML][HTML] Real-time big data processing for instantaneous marketing decisions: A problematization approach
The collection of big data from different sources such as the internet of things, social media
and search engines has created significant opportunities for business-to-business (B2B) …
and search engines has created significant opportunities for business-to-business (B2B) …
kNN-IS: An Iterative Spark-based design of the k-Nearest Neighbors classifier for big data
Abstract The k-Nearest Neighbors classifier is a simple yet effective widely renowned
method in data mining. The actual application of this model in the big data domain is not …
method in data mining. The actual application of this model in the big data domain is not …
ElStream: An ensemble learning approach for concept drift detection in dynamic social big data stream learning
With the rapid increase in communication technologies and smart devices, an enormous
surge in data traffic has been observed. A huge amount of data gets generated every …
surge in data traffic has been observed. A huge amount of data gets generated every …
Use and adaptations of machine learning in big data—Applications in real cases in agriculture
The data generated in modern agricultural operations are provided by diverse elements,
which allow a better understanding of the dynamic conditions of the crop, soil and climate …
which allow a better understanding of the dynamic conditions of the crop, soil and climate …
A general perspective of Big Data: applications, tools, challenges and trends
Big Data has become a very popular term. It refers to the enormous amount of structured,
semi-structured and unstructured data that are exponentially generated by high …
semi-structured and unstructured data that are exponentially generated by high …