Sustainable management of sweet potatoes: A review on practices, strategies, and opportunities in nutrition-sensitive agriculture, energy security, and quality of life
ABSTRACT CONTEXT Sweet potatoes are sources of staple food for human nutrition and
welfare. Hence, they can assist in develo** food security in vulnerable communities …
welfare. Hence, they can assist in develo** food security in vulnerable communities …
Machine learning can guide food security efforts when primary data are not available
Estimating how many people are food insecure and where they are is of fundamental
importance for governments and humanitarian organizations to make informed and timely …
importance for governments and humanitarian organizations to make informed and timely …
Ic-gan: An improved conditional generative adversarial network for rgb-to-ir image translation with applications to forest fire monitoring
This paper introduces a novel Deep Learning (DL) architecture for inferring temperature
information from aerial true-color RGB images by transforming them into Infrared Radiation …
information from aerial true-color RGB images by transforming them into Infrared Radiation …
[HTML][HTML] Forecasting disruptions in global food value chains to tackle food insecurity: The role of AI and big data analytics–A bibliometric and scientometric analysis
Globalization and interconnected supply chains have led to complex disruptions in global
value chains, caused by various factors such as natural disasters, climate events …
value chains, caused by various factors such as natural disasters, climate events …
Future food production prediction using AROA based hybrid deep learning model in agri-sector
S Baswaraju, VU Maheswari, K Chennam… - Human-Centric …, 2023 - Springer
Policymaking and administration of national tactics of action for food security rely heavily on
advances in models for accurate estimation of food output. In several fields, including food …
advances in models for accurate estimation of food output. In several fields, including food …
Advances in remote sensing based soil moisture retrieval: applications, techniques, scales and challenges for combining machine learning and physical models
Soil Moisture (SM) monitoring is crucial for various applications in agriculture, hydrology,
and climate science. Remote Sensing (RS) offers a powerful tool for large-scale SM …
and climate science. Remote Sensing (RS) offers a powerful tool for large-scale SM …
Machine learning for food security: current status, challenges, and future perspectives
A significant amount of study has been conducted on food security forecasting, yet, few
systematic reviews of the literature in this context are available. Recently, Machine Learning …
systematic reviews of the literature in this context are available. Recently, Machine Learning …
A novel cryptocurrency price time series hybrid prediction model via machine learning with MATLAB/Simulink
L Zhao, Z Li, Y Ma, L Qu - The Journal of Supercomputing, 2023 - Springer
Bitcoin is widely recognized as the first decentralized digital cryptocurrency based on
blockchain technology. Its unique properties make it a leading contender in the realm of …
blockchain technology. Its unique properties make it a leading contender in the realm of …
Classification of wheat varieties with image-based deep learning
Wheat is an important grain in the food chain. It is important in terms of efficiency and
economy to use wheat in the appropriate area according to its varieties. Breeding studies …
economy to use wheat in the appropriate area according to its varieties. Breeding studies …
[HTML][HTML] A dual-attention based coupling network for diabetes classification with heterogeneous data
Diabetes Mellitus (DM) is a group of metabolic disorders characterized by hyperglycaemia in
the absence of treatment. Classification of DM is essential as it corresponds to the respective …
the absence of treatment. Classification of DM is essential as it corresponds to the respective …