Application of artificial intelligence in food industry—a guideline

NR Mavani, JM Ali, S Othman, MA Hussain… - Food Engineering …, 2022‏ - Springer
Artificial intelligence (AI) has embodied the recent technology in the food industry over the
past few decades due to the rising of food demands in line with the increasing of the world …

[HTML][HTML] The application of artificial intelligence and big data in the food industry

H Ding, J Tian, W Yu, DI Wilson, BR Young, X Cui… - Foods, 2023‏ - mdpi.com
Over the past few decades, the food industry has undergone revolutionary changes due to
the impacts of globalization, technological advancements, and ever-evolving consumer …

Breast tumor localization and segmentation using machine learning techniques: Overview of datasets, findings, and methods

R Ranjbarzadeh, S Dorosti, SJ Ghoushchi… - Computers in Biology …, 2023‏ - Elsevier
Abstract The Global Cancer Statistics 2020 reported breast cancer (BC) as the most
common diagnosis of cancer type. Therefore, early detection of such type of cancer would …

A new complex fuzzy inference system with fuzzy knowledge graph and extensions in decision making

LTH Lan, TM Tuan, TT Ngan, NL Giang… - Ieee …, 2020‏ - ieeexplore.ieee.org
Context and Background: Complex fuzzy theory has a strong practical implication in many
real-world applications. Complex Fuzzy Inference System (CFIS) is a powerful technique to …

Hybrid multi-criteria decision-making approach to select appropriate biomass resources for biofuel production

S Firouzi, MS Allahyari, M Isazadeh, A Nikkhah… - Science of the Total …, 2021‏ - Elsevier
Biofuel generation from local biomass resources can significantly contribute to greenhouse
gas mitigation and cleaner energy production. In this regard, a hybrid Multi-Criteria Decision …

Classification of oolong tea varieties based on computer vision and convolutional neural networks

Y Zhu, S Chen, H Yin, X Han, M Xu… - Journal of the …, 2024‏ - Wiley Online Library
BACKGROUND In the contemporary food industry, accurate and rapid differentiation of
oolong tea varieties holds paramount importance for traceability and quality control …

[HTML][HTML] Tea category identification using wavelet signal reconstruction of hyperspectral imagery and machine learning

Q Cui, B Yang, B Liu, Y Li, J Ning - Agriculture, 2022‏ - mdpi.com
Accurately distinguishing the types of tea is of great significance to the pricing, production,
and processing of tea. The similarity of the internal spectral characteristics and appearance …

An instance-based deep transfer learning method for quality identification of Long**g tea from multiple geographical origins

C Zhang, J Wang, T Yan, X Lu, G Lu, X Tang… - Complex & Intelligent …, 2023‏ - Springer
For practitioners, it is very crucial to realize accurate and automatic vision-based quality
identification of Long**g tea. Due to the high similarity between classes, the classification …

A novel fuzzy knowledge graph pairs approach in decision making

CK Long, P Van Hai, TM Tuan, LTH Lan… - Multimedia Tools and …, 2022‏ - Springer
Abstract Fuzzy Knowledge Graph (FKG) has recently been emerging as one of the key
techniques for supporting classification and decision-making problems. FKG is a novel …

[HTML][HTML] Classification of tea leaves based on fluorescence imaging and convolutional neural networks

K Wei, B Chen, Z Li, D Chen, G Liu, H Lin, B Zhang - Sensors, 2022‏ - mdpi.com
The development of the smartphone and computer vision technique provides customers with
a convenient approach to identify tea species, as well as qualities. However, the prediction …