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Discriminant Analysis

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Rapid detection of colored and colorless macro- and micro-plastics in complex environment via near-infrared spectroscopy and machine learning.

Journal of environmental sciences (China)
To better understand the migration behavior of plastic fragments in the environment, development of rapid non-destructive methods for in-situ identification and characterization of plastic fragments is necessary. However, most of the studies had focu...

Improving Hand Gesture Recognition Robustness to Dynamic Posture Variations by Multimodal Deep Feature Fusion.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Surface electromyography (sEMG), a human-machine interface for gesture recognition, has shown promising potential for decoding motor intentions, but a variety of nonideal factors restrict its practical application in assistive robots. In this paper, ...

DeepIDA-GRU: a deep learning pipeline for integrative discriminant analysis of cross-sectional and longitudinal multiview data with applications to inflammatory bowel disease classification.

Briefings in bioinformatics
Biomedical research now commonly integrates diverse data types or views from the same individuals to better understand the pathobiology of complex diseases, but the challenge lies in meaningfully integrating these diverse views. Existing methods ofte...

Improved Classification Performance of Bacteria in Interference Using Raman and Fourier-Transform Infrared Spectroscopy Combined with Machine Learning.

Molecules (Basel, Switzerland)
The rapid and sensitive detection of pathogenic and suspicious bioaerosols are essential for public health protection. The impact of pollen on the identification of bacterial species by Raman and Fourier-Transform Infrared (FTIR) spectra cannot be ov...

Non-destructive prediction of fertility and sex in chicken eggs using the short wave near-infrared region.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
The objective of this study was to evaluate the ability of a handheld near-infrared device (900-1600 nm) to predict fertility and sex (male and female) traits in-ovo. The NIR reflectance spectra of the egg samples were collected on days 0, 7, 14 and ...

Molecular separation-assisted label-free SERS combined with machine learning for nasopharyngeal cancer screening and radiotherapy resistance prediction.

Journal of photochemistry and photobiology. B, Biology
Nasopharyngeal cancer (NPC) is a malignant tumor with high prevalence in Southeast Asia and highly invasive and metastatic characteristics. Radiotherapy is the primary strategy for NPC treatment, however there is still lack of effect method for predi...

Polygonati Rhizoma varieties and origins traceability based on multivariate data fusion combined with an artificial intelligence classification algorithm.

Food chemistry
This study collected multidimensional feature data such as spectra, texture, and component contents of Polygonati Rhizoma from different origins and varieties (Polygonatum kingianum Coll. et Hemsl from Yunnan and Guizhou; Polygonatum cyrtonema Hua fr...

Functional data geometric morphometrics with machine learning for craniodental shape classification in shrews.

Scientific reports
This work proposes a functional data analysis approach for morphometrics in classifying three shrew species (S. murinus, C. monticola, and C. malayana) from Peninsular Malaysia. Functional data geometric morphometrics (FDGM) for 2D landmark data is i...

Sugarcane disease recognition through visible and near-infrared spectroscopy using deep learning assisted continuous wavelet transform-based spectrogram.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Utilizing visible and near-infrared (Vis-NIR) spectroscopy in conjunction with chemometrics methods has been widespread for identifying plant diseases. However, a key obstacle involves the extraction of relevant spectral characteristics. This study a...

Euclidean-Distance-Preserved Feature Reduction for efficient person re-identification.

Neural networks : the official journal of the International Neural Network Society
Person Re-identification (Re-ID) aims to match person images across non-overlapping cameras. The existing approaches formulate this task as fine-grained representation learning with deep neural networks, which involves extracting image features using...