H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Engineering and Technology D-index 55 Citations 9,526 450 World Ranking 975 National Ranking 100

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Statistics
  • Internal medicine

His main research concerns Analytical chemistry, Near-infrared spectroscopy, Partial least squares regression, Hyperspectral imaging and Linear regression. His Analytical chemistry research includes themes of Correlation coefficient, Mean squared error, Chromatography, Residual and Calibration. His Near-infrared spectroscopy research includes elements of Principal component analysis, Least squares support vector machine and Fingerprint.

His research in Principal component analysis intersects with topics in Artificial neural network, Wavelet transform, Support vector machine and Dimensionality reduction. The study incorporates disciplines such as Regression analysis, Biological system, Tartaric acid and Chemometrics in addition to Partial least squares regression. Remote sensing and Artificial intelligence are the focus of his Hyperspectral imaging studies.

His most cited work include:

  • Theory and application of near infrared reflectance spectroscopy in determination of food quality (592 citations)
  • Non-destructive measurement of acidity, soluble solids and firmness of Satsuma mandarin using Vis/NIR-spectroscopy techniques (257 citations)
  • Study on infrared spectroscopy technique for fast measurement of protein content in milk powder based on LS-SVM (167 citations)

What are the main themes of his work throughout his whole career to date?

Yong He mostly deals with Partial least squares regression, Artificial intelligence, Analytical chemistry, Near-infrared spectroscopy and Principal component analysis. His work investigates the relationship between Partial least squares regression and topics such as Correlation coefficient that intersect with problems in Mean squared error. His studies in Artificial intelligence integrate themes in fields like Computer vision and Pattern recognition.

His work deals with themes such as Smoothing, Laser-induced breakdown spectroscopy and Least squares support vector machine, which intersect with Analytical chemistry. Yong He combines subjects such as Vis nir spectroscopy, Wavelet transform and Cluster analysis with his study of Principal component analysis. His Hyperspectral imaging research is multidisciplinary, incorporating elements of Region of interest and Pixel.

He most often published in these fields:

  • Partial least squares regression (24.36%)
  • Artificial intelligence (22.91%)
  • Analytical chemistry (21.34%)

What were the highlights of his more recent work (between 2017-2021)?

  • Artificial intelligence (22.91%)
  • Hyperspectral imaging (16.09%)
  • Pattern recognition (17.88%)

In recent papers he was focusing on the following fields of study:

The scientist’s investigation covers issues in Artificial intelligence, Hyperspectral imaging, Pattern recognition, Partial least squares regression and Principal component analysis. His research related to Support vector machine, Deep learning, Convolutional neural network, Segmentation and Feature extraction might be considered part of Artificial intelligence. The various areas that he examines in his Hyperspectral imaging study include Extreme learning machine and Linear discriminant analysis.

Specifically, his work in Pattern recognition is concerned with the study of Feature selection. His Partial least squares regression study necessitates a more in-depth grasp of Analytical chemistry. The Laser-induced breakdown spectroscopy study combines topics in areas such as Soil test, Multivariate statistics, Correlation coefficient and Chemometrics.

Between 2017 and 2021, his most popular works were:

  • Overview of recent advances in stability of linear systems with time‐varying delays (91 citations)
  • Variety Identification of Single Rice Seed Using Hyperspectral Imaging Combined with Convolutional Neural Network (70 citations)
  • Sampled-data-based dissipative control of T-S fuzzy systems (67 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Statistics
  • Internal medicine

Yong He focuses on Hyperspectral imaging, Artificial intelligence, Pattern recognition, Partial least squares regression and Principal component analysis. Yong He has included themes like Extreme learning machine, Linear discriminant analysis, Computational biology and Least squares support vector machine in his Hyperspectral imaging study. His study in Pattern recognition is interdisciplinary in nature, drawing from both Pixel and Feature.

His study on Partial least squares regression is covered under Analytical chemistry. His biological study spans a wide range of topics, including Residue, Fourier transform and Near-infrared spectroscopy. He interconnects Visualization, Accelerated aging, Wavelet transform and Germination in the investigation of issues within Principal component analysis.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Theory and application of near infrared reflectance spectroscopy in determination of food quality

Haiyan Cen;Yong He.
Trends in Food Science and Technology (2007)

923 Citations

Non-destructive measurement of acidity, soluble solids and firmness of Satsuma mandarin using Vis/NIR-spectroscopy techniques

Antihus Hernández Gómez;Yong He;Annia García Pereira.
Journal of Food Engineering (2006)

387 Citations

Discrimination of varieties of tea using near infrared spectroscopy by principal component analysis and BP model

Yong He;Xiaoli Li;Xunfei Deng.
Journal of Food Engineering (2007)

272 Citations

Study on infrared spectroscopy technique for fast measurement of protein content in milk powder based on LS-SVM

Di Wu;Yong He;Shuijuan Feng;Da-Wen Sun.
Journal of Food Engineering (2008)

231 Citations

Application of Visible and Near Infrared Hyperspectral Imaging to Differentiate Between Fresh and Frozen–Thawed Fish Fillets

Fengle Zhu;Derong Zhang;Yong He;Fei Liu.
Food and Bioprocess Technology (2013)

197 Citations

Rapid prediction of moisture content of dehydrated prawns using online hyperspectral imaging system

Di Wu;Di Wu;Hui Shi;Songjing Wang;Yong He.
Analytica Chimica Acta (2012)

184 Citations

Delay-dependent stability analysis of neural networks with time-varying delay

Chuan-Ke Zhang;Yong He;Lin Jiang;Wen-Juan Lin.
Applied Mathematics and Computation (2017)

179 Citations

Hybrid variable selection in visible and near-infrared spectral analysis for non-invasive quality determination of grape juice.

Di Wu;Yong He;Pengcheng Nie;Pengcheng Nie;Fang Cao.
Analytica Chimica Acta (2010)

177 Citations

Application of long-wave near infrared hyperspectral imaging for measurement of color distribution in salmon fillet

Di Wu;Da-Wen Sun;Yong He.
Innovative Food Science and Emerging Technologies (2012)

175 Citations

Prediction of soil macronutrients content using near-infrared spectroscopy

Yong He;Min Huang;Annia García;Antihus Hernández.
Computers and Electronics in Agriculture (2007)

169 Citations

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