Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Towards leveraging the role of machine learning and artificial intelligence in precision agriculture and smart farming
The digitalization of data has resulted in a data tsunami in practically every industry of data-
driven enterprise. Furthermore, man-to-machine (M2M) digital data handling has …
driven enterprise. Furthermore, man-to-machine (M2M) digital data handling has …
[HTML][HTML] Crop yield prediction using machine learning: A systematic literature review
Abstract Machine learning is an important decision support tool for crop yield prediction,
including supporting decisions on what crops to grow and what to do during the growing …
including supporting decisions on what crops to grow and what to do during the growing …
A comprehensive review of crop yield prediction using machine learning approaches with special emphasis on palm oil yield prediction
An early and reliable estimation of crop yield is essential in quantitative and financial
evaluation at the field level for determining strategic plans in agricultural commodities for …
evaluation at the field level for determining strategic plans in agricultural commodities for …
Remote-sensing data and deep-learning techniques in crop map** and yield prediction: A systematic review
Reliable and timely crop-yield prediction and crop map** are crucial for food security and
decision making in the food industry and in agro-environmental management. The global …
decision making in the food industry and in agro-environmental management. The global …
Machine learning for smart agriculture and precision farming: towards making the fields talk
In almost every sector, data-driven business, the digitization of the data has generated a
data tsunami. In addition, man-to-machine digital data handling has magnified the …
data tsunami. In addition, man-to-machine digital data handling has magnified the …
Integrating multi-source data for rice yield prediction across China using machine learning and deep learning approaches
Timely and reliable yield prediction at a large scale is imperative and prerequisite to prevent
climate risk and ensure food security, especially with climate change and increasing …
climate risk and ensure food security, especially with climate change and increasing …
[HTML][HTML] Integrated phenology and climate in rice yields prediction using machine learning methods
Rice (Oryza sativa L.) is a staple cereal crop and its demand is substantially increasing with
the growth of the global population. Precisely predicting rice yields are of vital importance to …
the growth of the global population. Precisely predicting rice yields are of vital importance to …
Uniting remote sensing, crop modelling and economics for agricultural risk management
The increasing availability of satellite data at higher spatial, temporal and spectral
resolutions is enabling new applications in agriculture and economic development …
resolutions is enabling new applications in agriculture and economic development …
Winter wheat yield prediction using convolutional neural networks from environmental and phenological data
Crop yield forecasting depends on many interactive factors, including crop genotype,
weather, soil, and management practices. This study analyzes the performance of machine …
weather, soil, and management practices. This study analyzes the performance of machine …
Forecasting vegetation indices from spatio-temporal remotely sensed data using deep learning-based approaches: A systematic literature review
Over the last few years, Deep learning (DL) approaches have been shown to outperform
state-of-the-art machine learning (ML) techniques in many applications such as vegetation …
state-of-the-art machine learning (ML) techniques in many applications such as vegetation …