Application of deep learning in multitemporal remote sensing image classification

X Cheng, Y Sun, W Zhang, Y Wang, X Cao, Y Wang - Remote Sensing, 2023 - mdpi.com
The rapid advancement of remote sensing technology has significantly enhanced the
temporal resolution of remote sensing data. Multitemporal remote sensing image …

A research review on deep learning combined with hyperspectral Imaging in multiscale agricultural sensing

L Shuai, Z Li, Z Chen, D Luo, J Mu - Computers and Electronics in …, 2024 - Elsevier
Efficient and automated data acquisition techniques, as well as intelligent and accurate data
processing and analysis techniques, are essential for the advancement of precision …

[HTML][HTML] Rapidly and accurately determining the resin and volatile content of CF/PPBESK thermoplastic prepreg by NIR spectroscopy

H Hao, S Cheng, Z Ren, L Zhang, B Wang, N Li… - Composites Part A …, 2023 - Elsevier
In this study, near infrared (NIR) spectroscopy was used to predict the resin content and
volatile content of CF/PPBESK prepreg. Mathematical models between resin and volatile …

Evaluating the dry matter content of raw yams using hyperspectral imaging spectroscopy and machine learning

M Adesokan, B Otegbayo, EO Alamu… - Journal of Food …, 2024 - Elsevier
Yams (Dioscorea spp.) are important food and commercial crops in West African countries.
They contribute significantly to global food production and provide dietary energy. The …

A brief history of remote sensing of soybean

JM Prince Czarnecki, S Samiappan… - Agronomy …, 2025 - Wiley Online Library
The last 20 years have been a period of significant advancement in the tools available for
remote sensing of soybean [Glycine max (L.) Merr.] in terms of price, ease of use, quality of …

Improved retrieval of phylogenetic signals from normalized foliar reflectance spectra in Neotropical forest gaps

ÉS Diniz, CH do Amaral, LA de Almeida Telles… - Community …, 2023 - Springer
Distinct data pre-processing techniques affect features derived from spectral data, such as
the occurrence of phylogenetic signals in the foliar spectra. This study investigates how …

Interpretable Machine-Learning for Predicting Molecular Weight of PLA Based on Artificial Bee Colony Optimization Algorithm and Adaptive Neurofuzzy Inference …

AP Masoumi, L Creedon, R Ghosh… - 2024 35th Irish …, 2024 - ieeexplore.ieee.org
This article discusses the integration of the artificial bee colony (ABC) algorithm with two
supervised learning methods, namely artificial neural network (ANN) and adaptive network …