Analysis of the multilayer organization of a sunflower leaf during dehydration with terahertz time-domain spectroscopy

Article Optics

Artificial neural networks for material parameter extraction in terahertz time-domain spectroscopy

Nicholas Klokkou et al.

Summary: Researchers have trained an artificial neural network using a large dataset of simulated light-matter interactions, which provides a computationally efficient method for accurately extracting material parameters in THz-TDS. This method is easier to implement and faster to run than traditional methods, and can address common issues in analyzing THz-TDS data.

OPTICS EXPRESS (2022)

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Article Chemistry, Analytical

Translation-Invariant Zero-Phase Wavelet Methods for Feature Extraction in Terahertz Time-Domain Spectroscopy

Mahmoud E. Khani et al.

Summary: Wavelet transform plays an important role in terahertz time-domain spectroscopy (THz-TDS) measurements. This paper investigates the effects of using different forms of wavelet transforms in THz-TDS studies. It is found that the spectroscopic features extracted using discrete wavelet transform (DWT) can vary over different frequency ranges, while the maximal overlap discrete wavelet transform (MODWT) is translation-invariant and yields identical features regardless of the spectral range. Additionally, MODWT provides zero-phase filters for multiresolution analysis (MRA), whereas DWT suffers from misalignments caused by downsampling and upsampling operations in the pyramid algorithm.

SENSORS (2022)

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Review Plant Sciences

Robotic Technologies for High-Throughput Plant Phenotyping: Contemporary Reviews and Future Perspectives

Abbas Atefi et al.

Summary: Phenotyping plants using robots has revolutionized the traditional manual measurement methods, providing a more efficient way to monitor changes in plant traits. However, the operation of these robots still faces challenges due to the dynamic nature of plants and agricultural environments.

FRONTIERS IN PLANT SCIENCE (2021)

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Review Agriculture, Multidisciplinary