An Optimal Faster Region-Based Convolutional Neural Network for Oil Adulteration Detection

• Published in: Arabian journal for science and engineering (2011) Vol. 48; no. 2; pp. 2231 - 2245
• Main Authors: Surya, V., Senthilselvi, A.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.02.2023; Springer Nature B.V
• Subjects: Artificial neural networks; Engineering; Humanities and Social Sciences; multidisciplinary; Neural networks; Rapeseed; Research Article-Computer Engineering and Computer Science; Science; Vegetable oils; Oil adulteration; War strategy optimization algorithm; Chemometric methods; Excitation-emission matrix fluorescence; Faster region-based convolutional neural network

Natural oils such as avocado oil (AO), corn oil (CO), chamomile oil (CMO), and rapeseed oil (RSO) are used for improving health, skin, and hair care for centuries in different parts of the world. The AO, CO, and RSO oil are known for their antibacterial and moisturizing properties. The growth of the...