The emerging role of Raman spectroscopy as an omics approach for metabolic profiling and biomarker detection toward precision medicine
Omics technologies have rapidly evolved with the unprecedented potential to shape
precision medicine. Novel omics approaches are imperative toallow rapid and accurate data …
precision medicine. Novel omics approaches are imperative toallow rapid and accurate data …
Food and agro-product quality evaluation based on spectroscopy and deep learning: A review
Background Rapid and non-destructive infrared spectroscopy has been applied to both
internal and external quality evaluations of food and agro-products. Various linear and …
internal and external quality evaluations of food and agro-products. Various linear and …
Deep learning for biospectroscopy and biospectral imaging: state-of-the-art and perspectives
With the advances in instrumentation and sampling techniques, there is an explosive growth
of data from molecular and cellular samples. The call to extract more information from the …
of data from molecular and cellular samples. The call to extract more information from the …
Deep learning approaches and interventions for futuristic engineering in agriculture
With shrinking natural resources and the climate challenges, it is foreseen that there will be
an imminent stress in agricultural outputs. Deep learning provides immense possibilities in …
an imminent stress in agricultural outputs. Deep learning provides immense possibilities in …
Hybrid 1D-CNN and attention-based Bi-GRU neural networks for predicting moisture content of sand gravel using NIR spectroscopy
Q Yuan, J Wang, M Zheng, X Wang - Construction and Building Materials, 2022 - Elsevier
A non-destructive and rapid moisture content detection method of sand gravel material is
required in loose material dams. The near-infrared (NIR) spectrum of sand materials is …
required in loose material dams. The near-infrared (NIR) spectrum of sand materials is …
Interpretable deep learning-assisted laser-induced breakdown spectroscopy for brand classification of iron ores
W Zhao, C Li, C Yan, H Min, Y An, S Liu - Analytica chimica acta, 2021 - Elsevier
Brand classification of iron ores using laser-induced breakdown spectroscopy (LIBS)
combined with artificial neural networks can quickly realize the compliance verification and …
combined with artificial neural networks can quickly realize the compliance verification and …
A deep learning approach for detecting colorectal cancer via Raman spectra
Objective and Impact Statement. Distinguishing tumors from normal tissues is vital in the
intraoperative diagnosis and pathological examination. In this work, we propose to utilize …
intraoperative diagnosis and pathological examination. In this work, we propose to utilize …
Classification of pathogens by Raman spectroscopy combined with generative adversarial networks
Rapid identification of marine pathogens is very important in marine ecology. Artificial
intelligence combined with Raman spectroscopy is a promising choice for identifying marine …
intelligence combined with Raman spectroscopy is a promising choice for identifying marine …
Principles and applications of convolutional neural network for spectral analysis in food quality evaluation: A review
N Luo, D Xu, B Xing, X Yang, C Sun - Journal of Food Composition and …, 2024 - Elsevier
The spectroscopic technologies have been successfully applied to food quality evaluation
owing to their abilities of wavelengths being sensitive to biological components of food, and …
owing to their abilities of wavelengths being sensitive to biological components of food, and …
Identification of soybean varieties using hyperspectral imaging coupled with convolutional neural network
S Zhu, L Zhou, C Zhang, Y Bao, B Wu, H Chu, Y Yu… - Sensors, 2019 - mdpi.com
Soybean variety is connected to stress resistance ability, as well as nutritional and
commercial value. Near-infrared hyperspectral imaging was applied to classify three …
commercial value. Near-infrared hyperspectral imaging was applied to classify three …