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Food

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Mediterranean Food Image Recognition Using Deep Convolutional Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
We present a new dataset of food images that can be used to evaluate food recognition systems and dietary assessment systems. The Mediterranean Greek food -MedGRFood dataset consists of food images from the Mediterranean cuisine, and mainly from the ...

Machine learning predicts the effect of food on orally administered medicines.

International journal of pharmaceutics
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...

GourmetNet: Food Segmentation Using Multi-Scale Waterfall Features with Spatial and Channel Attention.

Sensors (Basel, Switzerland)
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...

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
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...

The fourth industrial revolution in the food industry-Part I: Industry 4.0 technologies.

Critical reviews in food science and nutrition
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...

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

International journal of food microbiology
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,...

Deep learning accurately predicts food categories and nutrients based on ingredient statements.

Food chemistry
Determining attributes such as classification, creating taxonomies and nutrients for foods can be a challenging and resource-intensive task, albeit important for a better understanding of foods. In this study, a novel dataset, 134 k BFPD, was collect...

Design of experiments meets immersive environment: Optimising eating atmosphere using artificial neural network.

Appetite
Design of experiments (DOE) is a family of statistical tools commonly used in food science to optimise recipes and facilitate new food development. In a novel cross-disciplinary twist, we propose to adapt DOE approach to the optimisation of restauran...

Development and validation of a chewing robot for mimicking human food oral processing and producing food bolus.

Journal of texture studies
More and more studies have being done on the deformation process of food and the formation of food bolus during chewing. However, it is hard to observe the food oral processing (FOP) of subjects and obtain related data directly. A bionic chewing robo...

Anti-Jamming Strategy for Federated Learning in Internet of Medical Things: A Game Approach.

IEEE journal of biomedical and health informatics
Federated learning (FL) is a new dawn of artificial intelligence (AI), in which machine learning models are constructed in a distributed manner while communicating only model parameters between a centralized aggregator and client internet-of-medical-...