AIMC Topic: Nutrients

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An Exploratory Approach to Deriving Nutrition Information of Restaurant Food from Crowdsourced Food Images: Case of Hartford.

Nutrients
Deep learning models can recognize the food item in an image and derive their nutrition information, including calories, macronutrients (carbohydrates, fats, and proteins), and micronutrients (vitamins and minerals). This technology has yet to be imp...

Combining novel technologies with interdisciplinary basic research to enhance horticultural crops.

The Plant journal : for cell and molecular biology
Horticultural crops mainly include fruits, vegetables, ornamental trees and flowers, and tea trees (Melaleuca alternifolia). They produce a variety of nutrients for the daily human diet in addition to the nutrition provided by staple crops, and some ...

An Innovative Machine Learning Approach to Predict the Dietary Fiber Content of Packaged Foods.

Nutrients
Underconsumption of dietary fiber is prevalent worldwide and is associated with multiple adverse health conditions. Despite the importance of fiber, the labeling of fiber content on packaged foods and beverages is voluntary in most countries, making ...

Application of deep learning for image-based Chinese market food nutrients estimation.

Food chemistry
With commercialization of deep learning (DL) models, daily precision dietary record based on images from smartphones becomes possible. This study took advantage of DL techniques on visual recognition tasks and proposed a suite of big-data-driven DL m...

Machine Learning Strategy for Soil Nutrients Prediction Using Spectroscopic Method.

Sensors (Basel, Switzerland)
The research presented in this paper is based on the hypothesis that the machine learning approach improves the accuracy of soil properties prediction. The correlations obtained in this research are important for understanding the overall strategy fo...

Soil Nutrient Estimation and Mapping in Farmland Based on UAV Imaging Spectrometry.

Sensors (Basel, Switzerland)
Soil nutrient is one of the most important properties for improving farmland quality and product. Imaging spectrometry has the potential for rapid acquisition and real-time monitoring of soil characteristics. This study aims to explore the preprocess...

Application of ANN and SVM for prediction nutrients in rivers.

Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering
This paper presents the results of predicting nutrients in rivers on national level by the use of two artificial intelligence methodologies. Artificial neural network (ANN) and support vector machine (SVM) were used to predict annual concentration of...

Image-based nutrient estimation for Chinese dishes using deep learning.

Food research international (Ottawa, Ont.)
Food image recognition systems facilitate dietary assessment and in turn track users' dietary behaviors. However, due to the diversity of Chinese food, a quick and accurate food image recognizing is a particularly challenging task. The success of dee...

Artificial Intelligence in Nutrients Science Research: A Review.

Nutrients
Artificial intelligence (AI) as a branch of computer science, the purpose of which is to imitate thought processes, learning abilities and knowledge management, finds more and more applications in experimental and clinical medicine. In recent decades...

Combined effects of volume ratio and nitrate recycling ratio on nutrient removal, sludge characteristic and microbial evolution for DPR optimization.

Journal of environmental sciences (China)
The optimization of volume ratio (V/V/V) and nitrate recycling ratio (R) in a two-sludge denitrifying phosphorus removal (DPR) process of Anaerobic Anoxic Oxic-Moving Bed Biofilm Reactor (A/O-MBBR) was investigated. The results showed that prolonged ...