Unmasking honey adulteration : a breakthrough in quality assurance through cutting-edge convolutional neural network analysis of thermal images

Honey, a natural product generated from organic sources, is widely recognized for its revered reputation. Nevertheless, honey is susceptible to adulteration, a situation that has substantial consequences for both the well-being of the general population and the financial well-being of a country. Conventional approaches for detecting honey adulteration are often associated with extensive time requirements and restricted sensitivity. This paper presents a novel approach to address the aforementioned issue by employing Convolutional Neural Networks (CNNs) for the classification of honey …

analysis consequences convolutional neural network country cs.cv edge financial general generated images natural network neural network population product quality quality assurance through