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Author

Fu Qiao

ORCID: 0000-0002-1345-3709
Observed ORCID: 0000-0002-1345-3709
OpenAlex ID: A5079238094
Rapid detection of mussels contaminated by heavy metals using near-infrared reflectance spectroscopy and a constrained difference extreme learning machine
2021 · Yao Liu, Lele Xu, et al. · Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy · 31
Study on the detection of heavy metal lead (Pb) in mussels based on near-infrared spectroscopy technology and a REELM classifier
2022 · Yao Liu, Lele Xu, et al. · Microchemical Journal · 12
Fast Detection of Diarrhetic Shellfish Poisoning Toxins in Mussels Using NIR Spectroscopy and Improved Twin Support Vector Machines
2022 · Yao Liu, Fu Qiao, et al. · Frontiers in Marine Science · 10
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Detection of mussels contaminated with cadmium by near‐infrared reflectance spectroscopy based on RELS‐TSVM
2024 · Yao Liu, Fu Qiao, et al. · Journal of Food Science · 4
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Detection of paralytic shellfish toxins by near‐infrared spectroscopy based on a near‐Bayesian SVM classifier with unequal misclassification costs
2023 · Yao Liu, Jianfang Xiong, et al. · Journal of the Science of Food and Agriculture · 4
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Application of hyperspectral imaging technology for rapid identification of Ruditapes philippinarum contaminated by heavy metals
2021 · Yao Liu, Fu Qiao, et al. · RSC Advances · 3
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Identification of Perna viridis contaminated with diarrhetic shellfish poisoning toxins in vitro using NIRS and a discriminative non-negative representation-based classifier
2023 · Yao Liu, Zhongyan Liu, et al. · Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy · 2
A New Efficient Calibration Method for Binocular Camera
2016 · Zhongyan Liu, Junlong Fang, et al. · International Journal of Signal Processing Image Processing and Pattern Recognition · 2
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Multi-Feature Metric-Guided Mesh Simplification
2013 · Hailing Wang, Fu Qiao, et al. · Advances in intelligent systems and computing · 2
Research on Construction of a Model for Detecting and Warning Psychological Abnormalities in College Students Based on Support Vector Machine Classifier
2023 · Zhongyan Liu, Muxi Qiao, et al. · IEEE Eurasia Conference on IOT, Communication and Engineering (ECICE) · 1
Detection of Ruditapes Philippinarum contaminated by heavy metals based on hyperspectral image and multilayer perceptron
2021 · Fu Qiao, Bolin Hao, et al. · International Conference on Algorithms, High Performance Computing and Artificial Intelligence (AHPCAI) · 1
Research on Teaching Reform of Database Principles Course Based on the Integration of Post-Course-Competition-Certification and Digital Empowerment
2026 · Zhongyan Liu, Junjie Yang, et al. · Educational Innovation Research
Innovation and Practice of the VPC Teaching Paradigm for the Database Principles Course in the Context of Emerging Engineering Education
2026 · Zhongyan Liu, Junjie Yang, et al. · Contemporary Education Frontiers
Rapid detection of diarrhetic shellfish poisoning toxins in Perna Viridis using NIS and D2-BO-SVM classifier
2023 · Zhongyan Liu, Yao Liu, et al. · European Food Research and Technology
Phase diagram combined with improved fuzzy support vector machine for rapid and nondestructive detection of Diarrhetic shellfish poisoning
2023 · Wei Jiang, Yao Liu, et al. · Acta Scientiarum Polonorum Technologia Alimentaria
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A Rapid Detection Method of Toxins-Contaminated Mussels Based on Near-Infrared Spectroscopy Combined with Collaborative Representation Approaches
2023 · Fu Qiao, Yao Liu, et al. · SSRN Electronic Journal
Study on the Detection of Heavy Metal Lead (Pb) in Mussels Based On Near-Infrared Spectroscopy Technology and a Reelm Classifier
2022 · Yao Liu, Lele Xu, et al. · SSRN Electronic Journal
Study on the Detection of Heavy Metal Lead (Pb) in Mussels Based on Near-Infrared Spectroscopy Technology and a Reelm Classifier
2022 · Yao Liu, Lele Xu, et al. · SSRN Electronic Journal
A Rapid Detection Method of Toxins-Contaminated Mussels Based on Near-Infrared Spectroscopy Combined with Collaborative Representation Approaches
2022 · Fu Qiao, Yao Liu, et al. · SSRN Electronic Journal
Works count: 19
Citation count: 72
H-index: 4
I10-index: 3
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