Efficient extraction of deep image features using convolutional neural network (CNN) for applications in detecting and analysing complex food matrices-Reference-Cited by-同舟云学术

Efficient extraction of deep image features using convolutional neural network (CNN) for applications in detecting and analysing complex food matrices

Published:2021-07 Issue: Volume:113 Page:193-204
ISSN:0924-2244
Container-title:Trends in Food Science & Technology
language:en
Short-container-title:Trends in Food Science & Technology

Author:

Liu Yao,Pu Hongbin,Sun Da-Wen^ORCID

Publisher

Elsevier BV

Subject

Food Science,Biotechnology

Reference83 articles.

1. Estimating the composition of food nutrients from hyperspectral signals based on deep neural networks;Ahn;Sensors,2019

2. Detection of red-meat adulteration by deep spectral-spatial features in hyperspectral images;Al-Sarayreh;Journal of Imaging,2018

3. Potential of deep learning and snapshot hyperspectral imaging for classification of species in meat;Al-Sarayreh;Food Control,2020

4. Date fruit classification for robotic harvesting in a natural environment using deep learning;Altaheri;IEEE Access,2019

5. On the utilization of deep and ensemble learning to detect milk adulteration;Asseiss Neto;BioData Mining,2019

Cited by 157 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Transformative impact: Artificial intelligence in the evolving landscape of processed food - A concise review focusing on some food processing sectors;Food Control;2025-01

2. ConvColor DL: Concatenated convolutional and handcrafted color features fusion for beef quality identification;Food Chemistry;2024-12

3. A new paradigm in cigarette smoke detection: Rapid identification technique based on ATR-FTIR spectroscopy and GhostNet-α;Microchemical Journal;2024-10

4. Ingredient-guided multi-modal interaction and refinement network for RGB-D food nutrition assessment;Digital Signal Processing;2024-10

5. Array-optimized artificial olfactory sensor enabling cost-effective and non-destructive detection of mycotoxin-contaminated maize;Food Chemistry;2024-10