A hybrid approach to tea crop yield prediction using simulation models and machine learning
Tea (Camellia sinensis L.) is one of the most highly consumed beverages globally after
water. Several countries import large quantities of tea from other countries to meet domestic …
water. Several countries import large quantities of tea from other countries to meet domestic …
Anomaly detection on data streams for smart agriculture
Smart agriculture technologies are effective instruments for increasing farm sustainability
and production. They generate many spatial, temporal, and time-series data streams that …
and production. They generate many spatial, temporal, and time-series data streams that …
Machine Learning Application in Horticulture and Prospects for Predicting Fresh Produce Losses and Waste: A Review
The current review examines the state of knowledge and research on machine learning (ML)
applications in horticultural production and the potential for predicting fresh produce losses …
applications in horticultural production and the potential for predicting fresh produce losses …
Using generative module and pruning inference for the fast and accurate detection of apple flower in natural environments
Y Zhang, S He, S Wa, Z Zong, Y Liu - Information, 2021 - mdpi.com
Apple flower detection is an important project in the apple planting stage. This paper
proposes an optimized detection network model based on a generative module and pruning …
proposes an optimized detection network model based on a generative module and pruning …
A proposed framework for crop yield prediction using hybrid feature selection approach and optimized machine learning
M Abdel-salam, N Kumar, S Mahajan - Neural Computing and Applications, 2024 - Springer
Accurately predicting crop yield is essential for optimizing agricultural practices and
ensuring food security. However, existing approaches often struggle to capture the complex …
ensuring food security. However, existing approaches often struggle to capture the complex …
[HTML][HTML] Improved frost forecast using machine learning methods
JR Rozante, E Ramirez, D Ramirez… - Artificial Intelligence in …, 2023 - Elsevier
Frosts are one of the atmospheric phenomena with one of the larger negative effects on the
agricultural sector in the southern region of Brazil, therefore, an earlier forecast can minimize …
agricultural sector in the southern region of Brazil, therefore, an earlier forecast can minimize …
Soybean seed counting and broken seed recognition based on image sequence of falling seeds
Z Chen, W Fan, Z Luo, B Guo - Computers and Electronics in Agriculture, 2022 - Elsevier
Seed counting and broken seed identification are important tasks in evaluating seed quality.
In this study, we proposed a computational method designed to perform these two functions …
In this study, we proposed a computational method designed to perform these two functions …
Artificial intelligence early warnings of agricultural energy internet
X Fu, F Yang - Frontiers in Energy Research, 2022 - frontiersin.org
Electrification in agriculture is an effective way for China to build modern agriculture, and it
brings significant environmental and economic benefits (Fu and Yang, 2022). With the …
brings significant environmental and economic benefits (Fu and Yang, 2022). With the …
基于深度学习的河南冬小麦春季冻害识别及年代际变化特征模拟.
黄睿茜， 赵俊芳， 杨嘉琪， 彭慧文… - Chinese Journal of …, 2024 - search.ebscohost.com
采用深度学习长短时记忆模型LSTM, 基于中国重要冬小麦种植区河南省的99 个气象站点1981−
2020 年的气象, 作物, 灾情等多源数据, 识别河南冬小麦春季冻害发生情况, 探讨冬小麦春季冻害 …
2020 年的气象, 作物, 灾情等多源数据, 识别河南冬小麦春季冻害发生情况, 探讨冬小麦春季冻害 …
[PDF][PDF] Machine Learning Application in Horticulture and Prospects for Predicting Fresh Produce Losses and Waste: A Review. Plants 2024, 13, 1200
The current review examines the state of knowledge and research on machine learning (ML)
applications in horticultural production and the potential for predicting fresh produce losses …
applications in horticultural production and the potential for predicting fresh produce losses …