AIMC Topic: Color

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Trap colour strongly affects the ability of deep learning models to recognize insect species in images of sticky traps.

Pest management science Oct 8, 2024
BACKGROUND: The use of computer vision and deep learning models to automatically classify insect species on sticky traps has proven to be a cost- and time-efficient approach to pest monitoring. As different species are attracted to different colours,...
Color Insecta Insect Control Animals Deep Learning
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Development of analytical "aroma wheels" for Oolong tea infusions (Shuixian and Rougui) and prediction of dynamic aroma release and colour changes during "Chinese tea ceremony" with machine learning.

Food chemistry Oct 4, 2024
The flavour of tea as a worldwide popular beverage has been studied extensively. This study aimed to apply established flavour analysis techniques (GC-MS, GC-O-MS and APCI-MS/MS) in innovative ways to characterise the flavour profile of oolong tea in...
Odorants Taste Volatile Organic Compounds Tandem Mass Spectrometry Gas Chromatography-Mass Spectrometry Humans Flavoring Agents Machine Learning Camellia sinensis Tea Color
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Integrating deep learning and data fusion for enhanced oranges soluble solids content prediction using machine vision and Vis/NIR spectroscopy.

Food chemistry Oct 1, 2024
The visible/near infrared (Vis/NIR) spectrum will become distorted due to variations in sample color, thereby reducing the prediction accuracy of fruit composition. In this study, we aimed to develop a deep learning model with color correction capabi...
Deep Learning Neural Networks, Computer Color Spectroscopy, Near-Infrared Fruit
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Plant-based egg washes for use in baked goods: Machine learning and visual parameter analysis.

Journal of food science Sep 27, 2024
Pea protein is one potential environmentally sustainable way of recreating the functionality of eggs in coatings for baked goods. These coatings are commonly applied to enhance visual properties of baked goods that consumers desire, especially color ...
Pattern Recognition, Visual Pisum sativum Cooking Glycerol Color Eggs Random Forest Hydrogen-Ion Concentration Plant Proteins Machine Learning Time Factors Principal Component Analysis Neural Networks, Computer
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ARTIFICIAL INTELLIGENCE IN DENTAL SHADE-MATCHING SHOWS PROMISING POTENTIAL FOR PRECISION IN RESTORATIVE DENTISTRY, THOUGH REQUIRING FURTHER IMPROVEMENT.

The journal of evidence-based dental practice Sep 17, 2024
ARTICLE TITLE AND BIBLIOGRAPHIC INFORMATION: Shetty, S., et al. (2023). "Artificial intelligence systems in dental shade-matching: A systematic review." J Prosthodont. DOI: 10.1111/jopr.13805.
Prosthesis Coloring Humans Artificial Intelligence Color Systematic Reviews as Topic Dental Prosthesis Design Dental Restoration, Permanent
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Predictive modeling of rice milling degree for three typical Chinese rice varieties using interpretative machine learning methods.

Journal of food science Sep 1, 2024
Brown rice over-milling causes high economic and nutrient loss. The rice degree of milling (DOM) detection and prediction remain a challenge for moderate processing. In this study, a self-established grain image acquisition platform was built. Degree...
Machine Learning Edible Grain Oryza Food Handling China Image Processing, Computer-Assisted Color
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Introducing a novel approach to dental color reproduction using AI technology.

Journal of esthetic and restorative dentistry : official publication of the American Academy of Esthetic Dentistry ... [et al.] Aug 18, 2024
OBJECTIVE: This article aims to describe a systematic method for tooth color reproduction with ceramics restorations employing artificial intelligence (AI) software named Matisse. It provides a comprehensive analysis of the entire process, beginning ...
Color Ceramics Prosthesis Coloring Humans Software Artificial Intelligence Female Computer-Aided Design
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Metabolomic analysis combined with machine learning algorithms enables the evaluation of postharvest pecan color stability.

Food chemistry Aug 9, 2024
Nut kernel color is a crucial quality indicator affecting the consumers first impression of the product. While growing evidence suggests that plant phenolics and their derivatives are linked to nut kernel color, the compounds (biomarkers) responsible...
Machine Learning Color Algorithms Metabolomics Anthocyanins Flavonoids Carya
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Linked Color Imaging with Artificial Intelligence Improves the Detection of Early Gastric Cancer.

Digestive diseases (Basel, Switzerland) Aug 5, 2024
INTRODUCTION: Esophagogastroduodenoscopy is the most important tool to detect gastric cancer (GC). In this study, we developed a computer-aided detection (CADe) system to detect GC with white light imaging (WLI) and linked color imaging (LCI) modes a...
Endoscopy, Digestive System Early Detection of Cancer Color Sensitivity and Specificity Male Female Middle Aged Aged Diagnosis, Computer-Assisted Stomach Neoplasms Humans Deep Learning Artificial Intelligence
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Non-targeted metabolomics and explainable artificial intelligence: Effects of processing and color on coniferyl aldehyde levels in Eucommiae cortex.

Food chemistry Jul 25, 2024
Eucommia ulmoides, a plant native to China, is valued for its medicinal properties and has applications in food, health products, and traditional Chinese medicine. Processed Eucommiae Cortex (EC) has historically been a highly valued medicine. Ancien...
Artificial Intelligence Zingiber officinale Plant Extracts Metabolomics Aldehydes Eucommiaceae Color Food Handling
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