Výsledky vyhledávání

Akademický článek

Rapid Discrimination of Aging Year of Chenpi Based on Hyperspectral Images

Autor: Cheng LIU, Lulu ZHAO, Songbin ZHOU, Yisen LIU, Tingyou WANG

Publikováno v: Shipin gongye ke-ji, Vol 45, Iss 24, Pp 243-251 (2024)

Chenpi, or sun-dried mandarin orange peel, held significant economic and medicinal value, yet counterfeit and substandard products were prevalent in the current market. The aging year of Chenpi was a crucial quality indicator, but accurately determin

Externí odkaz: https://doaj.org/article/fa4a750177484f08b262bd84da99c802

Zobrazit plný text záznamu

Akademický článek

Industrialization progress and challenges of cultivated meat

Autor: Jiaqi Cai, Shouwei Wang, Yingying Li, Shengyan Dong, Jun Liang, Yisen Liu, Shilei Li

Publikováno v: Journal of Future Foods, Vol 4, Iss 2, Pp 119-127 (2024)

ABSTRACT: With its more sustainable production mode and higher healthy food supplying, cultivated meat is gradually regarded as the promising alternative meat food in future by human beings. Most of the countries in the planet had participated in the

Externí odkaz: https://doaj.org/article/7353f2872a114d96823c5f980cd8d054

Zobrazit plný text záznamu

Akademický článek

Proto-DS: A Self-Supervised Learning-Based Nondestructive Testing Approach for Food Adulteration with Imbalanced Hyperspectral Data

Autor: Kunkun Pang, Yisen Liu, Songbin Zhou, Yixiao Liao, Zexuan Yin, Lulu Zhao, Hong Chen

Publikováno v: Foods, Vol 13, Iss 22, p 3598 (2024)

Conventional food fraud detection using hyperspectral imaging (HSI) relies on the discriminative power of machine learning. However, these approaches often assume a balanced class distribution in an ideal laboratory environment, which is impractical

Externí odkaz: https://doaj.org/article/d500d32bf047451c9c8d41787a048c38

Zobrazit plný text záznamu

Akademický článek

A Low- and High-Resolution Terahertz Image Pair Construction Method With Gradient Fusion for Learning-Based Super-Resolution

Autor: Fei Yuan, Songbin Zhou, Taobo Cheng, Yisen Liu

Publikováno v: IEEE Access, Vol 10, Pp 132506-132514 (2022)

Quality and feature quantity of low- and high-resolution image pairs for training are directly related to performance of learning-based super-resolution methods. In order to accurately increase learning features to the low- and high-resolution image

Externí odkaz: https://doaj.org/article/23cf1841287b43f68aba25bb5beeac9c

Zobrazit plný text záznamu

Akademický článek

A Self-Supervised Anomaly Detector of Fruits Based on Hyperspectral Imaging

Autor: Yisen Liu, Songbin Zhou, Zhiyong Wan, Zefan Qiu, Lulu Zhao, Kunkun Pang, Chang Li, Zexuan Yin

Publikováno v: Foods, Vol 12, Iss 14, p 2669 (2023)

Hyperspectral imaging combined with chemometric approaches is proven to be a powerful tool for the quality evaluation and control of fruits. In fruit defect-detection scenarios, developing an unsupervised anomaly detection framework is vital, as defe

Externí odkaz: https://doaj.org/article/006ce8649ccc4b129561c51a93b569fa

Zobrazit plný text záznamu

Akademický článek

Detection of Adulteration in Infant Formula Based on Ensemble Convolutional Neural Network and Near-Infrared Spectroscopy

Autor: Yisen Liu, Songbin Zhou, Wei Han, Chang Li, Weixin Liu, Zefan Qiu, Hong Chen

Publikováno v: Foods, Vol 10, Iss 4, p 785 (2021)

Adulteration in dairy products has received world-wide attention, and at the same time, near infrared (NIR) spectroscopy has proven to be a promising tool for adulteration detection given its advantages of real-time response and non-destructive analy

Externí odkaz: https://doaj.org/article/e69ad4f68dad45e2b1d5cf7129b9ec9d

Zobrazit plný text záznamu

Updated Insights into Epilepsy Mechanism and Treatment

Autor: Manli Jian, Yisen Liu, Xiaoyu Shen

Publikováno v: Highlights in Science, Engineering and Technology. 36:1446-1452

Epilepsy is the most prevalent, persistent, and deadly kind of neurological disorder. affecting 65 million individuals globally. To update the current understanding about its pathophysiological processes, diagnosis, classification criteria, and treat

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::9a4ded124aa7a6cef904591c9aabe775
https://doi.org/10.54097/hset.v36i.6267

Zobrazit plný text záznamu

A Self-Supervised Anomaly Detector of Fruits Based on Hyperspectral Imaging

Autor: Yin, Yisen Liu, Songbin Zhou, Zhiyong Wan, Zefan Qiu, Lulu Zhao, Kunkun Pang, Chang Li, Zexuan

Publikováno v: Foods; Volume 12; Issue 14; Pages: 2669

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=multidiscipl::dc9f6de2a5cd0d2eed85390216597303

Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání