Machine learning techniques for the identification of risk factors associated with food insecurity among adults in Arab countries during the COVID-19 pandemic
Background A direct consequence of global warming, and strongly correlated with poor
physical and mental health, food insecurity is a rising global concern associated with low …
physical and mental health, food insecurity is a rising global concern associated with low …
A new hybrid model of deep learning ResNeXt-SVM for Weed Detection: Case study
B Jabir, N Falih - … Journal of Intelligent Information Technologies (IJIIT …, 2022 - igi-global.com
A set of experiments has shown that deep learning as well as traditional learning can be
used in the weed detection process and perform well, although sometimes these models …
used in the weed detection process and perform well, although sometimes these models …
[PDF][PDF] A comparison of machine learning and deep learning models for predicting household food security status
M Nigus, HL Shashirekha - IJEER, 2022 - academia.edu
░ ABSTRACT-ML and DL algorithms are becoming more popular to predict household food
security status, which can be used by the governments and policymakers of the country to …
security status, which can be used by the governments and policymakers of the country to …
Investigating the Association between Nutrient Intake and Food Insecurity among Children and Adolescents in Palestine Using Machine Learning Techniques
Food insecurity is a public health concern that affects children worldwide, yet it represents a
particular burden for low-and middle-income countries. This study aims to utilize machine …
particular burden for low-and middle-income countries. This study aims to utilize machine …
Farm Households Food Security Status Automation Through Supervised Learning Approach: A Look at Agroecological Farms
Food insecurity is a pervasive phenomenon in Africa, and the paradox is that it affects
farming households more than others. Although early and accurate detection of famine in …
farming households more than others. Although early and accurate detection of famine in …
Efficient and accurate food calorie measurement system using novel enhanced convolutional neural network compared over K-nearest neighbor algorithm
K Harish, EK Subramanian… - AIP Conference …, 2024 - pubs.aip.org
The research is focused on the analysis of food calorie measurement using a novel
improved convolutional neural network for better prediction of calorie content in food. A …
improved convolutional neural network for better prediction of calorie content in food. A …
Optimisation Of Hyperparameters In Regression Algorithm For Predictions Of Student Academic Performance
MN Aslam, ARL Astuti - Proceeding of …, 2024 - prosiding-icostec.respati.ac.id
Students' academic achievement is measured by test scores, knowledge, and skills gained
from formal education. The importance of identifying potential academic failures motivates …
from formal education. The importance of identifying potential academic failures motivates …
STATISTICAL WEIGHTING BASED MEASUREMENT FOR FOOD QUALITY AND SAFETY DIMENSION OF FOOD SECURITY AND EFFICIENCY ASSESSMENT
ST ZAFFER - 2022 - qspace.qu.edu.qa
The appropriate application of statistical approaches on a data set brings powerful results
and insights for solving food security problems for current and future generations. Moreover …
and insights for solving food security problems for current and future generations. Moreover …
“Deep Analytics” au service d'une agriculture digitale et de précision: Application à la détection des mauvaises herbes.
B JABIR - 2022 - toubkal.imist.ma
L'agriculture digitale est une révolution technologique du domaine agricole qui consiste à
digitaliser les processus et filière de l'agriculture, tout en profitant des technologies …
digitaliser les processus et filière de l'agriculture, tout en profitant des technologies …