AIMC Topic: Food

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Deciphering the blackbox of omics approaches and artificial intelligence in food waste transformation and mitigation.

International journal of food microbiology Apr 28, 2022
It is necessary to stop the wastage of food during any stage of food chain to resolve the challenge of starvation, hunger and malnutrition in the world. Inception of modern techniques like omics (metagenomics, proteomics, transcriptomics, wasteomics,...
Humans Artificial Intelligence Food Supply Child Agriculture Food Refuse Disposal
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The fourth industrial revolution in the food industry-Part I: Industry 4.0 technologies.

Critical reviews in food science and nutrition Feb 3, 2022
Climate change, the growth in world population, high levels of food waste and food loss, and the risk of new disease or pandemic outbreaks are examples of the many challenges that threaten future food sustainability and the security of the planet and...
Food Refuse Disposal Humans Internet Food Industry Artificial Intelligence
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Detecting the content of the bright blue pigment in cream based on deep learning and near-infrared spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Dec 16, 2021
The excessive content of additives in food is a radical problem that affects human health. However, traditional chemical methods are limited by a long cycle, low accuracy, and strong destructiveness, so a fast and accurate alternative is urgently nee...
Humans Food Deep Learning Least-Squares Analysis Neural Networks, Computer Spectroscopy, Near-Infrared
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Machine learning predicts the effect of food on orally administered medicines.

International journal of pharmaceutics Nov 28, 2021
Food-mediated changes to drug absorption, termed the food effect, are hard to predict and can have significant implications for the safety and efficacy of oral drug products in patients. Mimicking the prandial states of the human gastrointestinal tra...
Support Vector Machine Food Humans Machine Learning
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GourmetNet: Food Segmentation Using Multi-Scale Waterfall Features with Spatial and Channel Attention.

Sensors (Basel, Switzerland) Nov 11, 2021
We propose GourmetNet, a single-pass, end-to-end trainable network for food segmentation that achieves state-of-the-art performance. Food segmentation is an important problem as the first step for nutrition monitoring, food volume and calorie estimat...
Attention Food Neural Networks, Computer Image Processing, Computer-Assisted
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Research on the Characteristics of Food Impaction with Tight Proximal Contacts Based on Deep Learning.

Computational and mathematical methods in medicine Nov 5, 2021
OBJECTIVE: Based on deep learning, the characteristics of food impaction with tight proximal contacts were studied to guide the subsequent clinical treatment of occlusal adjustment. At the same time, digital model building, software measurement, and ...
Dental Occlusion Occlusal Adjustment Mastication Tooth Diseases Imaging, Three-Dimensional Food Computational Biology Middle Aged Models, Dental Humans Deep Learning Adult
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Explainable deep learning ensemble for food image analysis on edge devices.

Computers in biology and medicine Oct 27, 2021
Food recognition systems recently garnered much research attention in the relevant field due to their ability to obtain objective measurements for dietary intake. This feature contributes to the management of various chronic conditions. Challenges su...
Artificial Intelligence Deep Learning Image Processing, Computer-Assisted Food Neural Networks, Computer
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Prediction of biogas production in anaerobic co-digestion of organic wastes using deep learning models.

Water research Sep 24, 2021
Interest in anaerobic co-digestion (AcoD) has increased significantly in recent decades owing to enhanced biogas productivity due to the utilization of different organic wastes, such as food waste and sewage sludge. In this study, a robust AcoD model...
Refuse Disposal Biofuels Food Anaerobiosis Deep Learning Methane Bioreactors Sewage Digestion
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On the Prediction of Biogas Production from Vegetables, Fruits, and Food Wastes by ANFIS- and LSSVM-Based Models.

BioMed research international Sep 24, 2021
This study is aimed at modeling biodigestion systems as a function of the most influencing parameters to generate two robust algorithms on the basis of the machine learning algorithms, including adaptive network-based fuzzy inference system (ANFIS) a...
Food Refuse Disposal Support Vector Machine Linear Models Fuzzy Logic Biofuels Least-Squares Analysis Algorithms Fruit Computer Simulation Vegetables
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Research on Enhanced Detection of Benzoic Acid Additives in Liquid Food Based on Terahertz Metamaterial Devices.

Sensors (Basel, Switzerland) May 7, 2021
It is very important for human health to supervise the use of food additives, because excessive use of food additives will cause harm to the human body, especially lead to organ failures and even cancers. Therefore, it is important to realize high-se...
Humans Support Vector Machine Food Least-Squares Analysis Benzoic Acid
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