AIMC Topic: Color
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Porkolor: A deep learning framework for pork color classification.
Meat science
Dec 12, 2024
Pork color is crucial for assessing its safety and freshness, and traditional methods of observing through human eyes are inefficient and subjective. In recent years, several methods have been proposed based on computer vision and deep learning have ...
Machine-Learning-Based Spectral Modeling: A Biomimetic Guide for Enhancing Esthetics.
Journal of esthetic and restorative dentistry : official publication of the American Academy of Esthetic Dentistry ... [et al.]
Dec 8, 2024
OBJECTIVE: To provide guidelines and means for optimal coverage and distribution of computer models with 1-10 clusters, designed based on an in vivo extensive dental colorimetric database and compare the findings with some reputable shade guides.
Artificial intelligence-driven quantification of antibiotic-resistant Bacteria in food by color-encoded multiplex hydrogel digital LAMP.
Food chemistry
Dec 4, 2024
Antibiotic-resistant bacteria pose considerable risks to global health, particularly through transmission in the food chain. Herein, we developed the artificial intelligence-driven quantification of antibiotic-resistant bacteria in food using a color...
Regression prediction of tobacco chemical components during curing based on color quantification and machine learning.
Scientific reports
Nov 7, 2024
Color is one of the most important indicators to characteristic the quality of tobacco, which is strongly related to the variations of chemical components. In order to clarify the relationship between the changes of tobacco color and chemical compone...
Monitoring poultry social dynamics using colored tags: Avian visual perception, behavioral effects, and artificial intelligence precision.
Poultry science
Nov 5, 2024
Artificial intelligence (AI) in animal behavior and welfare research is on the rise. AI can detect behaviors and localize animals in video recordings, thus it is a valuable tool for studying social dynamics. However, maintaining the identity of indiv...
Nondestructive freshness prediction of large yellow croaker (Pseudosciaena crocea) using computer vision and machine learning techniques based on pupil color.
Journal of food science
Oct 30, 2024
Conventional methods for evaluating of fish freshness based on physiological and biochemical methods are often destructive, complicated, and costly. This study aimed to predict the freshness of large yellow croaker which was sampled every second day ...
Utilizing Pseudo Color Image to Improve the Performance of Deep Transfer Learning-Based Computer-Aided Diagnosis Schemes in Breast Mass Classification.
Journal of imaging informatics in medicine
Oct 25, 2024
The purpose of this study is to investigate the impact of using morphological information in classifying suspicious breast lesions. The widespread use of deep transfer learning can significantly improve the performance of the mammogram based CADx sch...
Integrating color histogram analysis and convolutional neural networks for skin lesion classification.
Computers in biology and medicine
Oct 12, 2024
The color of skin lesions is a crucial diagnostic feature for identifying malignant melanoma and other skin diseases. Typical colors associated with melanocytic lesions include tan, brown, black, red, white, and blue-gray. This study introduces a nov...
Fusion of visible and fluorescence imaging through deep neural network for color value prediction of pelletized red peppers.
Journal of food science
Oct 11, 2024
A non-destructive method for determining the color value of pelletized red peppers is crucial for pepper processing factories. This study aimed to investigate the potentiality of visible and fluorescence images for the determination of color value of...
Artificial intelligence as a tool for predicting the quality attributes of garlic (Allium sativum L.) slices during continuous infrared-assisted hot air drying.
Journal of food science
Oct 9, 2024
Effective drying methods are a highly suitable solution for ensuring stable food supply chains, reducing postharvest agricultural losses, and preventing the spoilage of perishable fruits and vegetables. Moreover, machine learning techniques are innov...
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