[HTML][HTML] Optimizing cellulase production from Aspergillus flavus using response surface methodology and machine learning models
The study aims to optimize cellulase (CMCase) production by Aspergillus flavus using wheat
straw, an abundantly available lignocellulosic waste, as a substrate. Three parameters, ie …
straw, an abundantly available lignocellulosic waste, as a substrate. Three parameters, ie …
Few-shot learning for fine-grained emotion recognition using physiological signals
Fine-grained emotion recognition can model the temporal dynamics of emotions, which is
more precise than predicting one emotion retrospectively for an activity (eg, video clip …
more precise than predicting one emotion retrospectively for an activity (eg, video clip …
Estimation of winter wheat crop growth parameters using time series Sentinel-1A SAR data
In the present study, Sentinel-1A Synthetic Aperture Radar analysis of time series data at C-
band was carried out to estimate the winter wheat crop growth parameters. Five different …
band was carried out to estimate the winter wheat crop growth parameters. Five different …
Dual-polarimetric C-band SAR data for land use/land cover classification by incorporating textural information
The work presented here showed a comprehensive evaluation of dual-polarimetric RISAT-1
data for land use/land cover (LULC) classification. The textural images were extracted with …
data for land use/land cover (LULC) classification. The textural images were extracted with …
Spectral matching techniques (SMTs) and automated cropland classification algorithms (ACCAs) for mapping croplands of Australia using MODIS 250-m time-series …
P Teluguntla, PS Thenkabail, J Xiong… - … Journal of Digital …, 2017 - Taylor & Francis
Mapping croplands, including fallow areas, are an important measure to determine the
quantity of food that is produced, where they are produced, and when they are produced (eg …
quantity of food that is produced, where they are produced, and when they are produced (eg …
Comprehensive evaluation of soil moisture retrieval models under different crop cover types using C-band synthetic aperture radar data
In the present study, random forest regression (RFR), support vector regression (SVR) and
artificial neural network regression (ANNR) models were evaluated for the retrieval of soil …
artificial neural network regression (ANNR) models were evaluated for the retrieval of soil …
Mapping the expansion of boom crops in mainland Southeast Asia using dense time stacks of Landsat data
We performed a multi-date composite change detection technique using a dense-time stack
of Landsat data to map land-use and land-cover change (LCLUC) in Mainland Southeast …
of Landsat data to map land-use and land-cover change (LCLUC) in Mainland Southeast …
Deploying multispectral remote sensing for multi‐temporal analysis of archaeological crop stress at Ravenshall, Fife, Scotland
C Moriarty, DC Cowley, T Wade… - Archaeological …, 2019 - Wiley Online Library
Diminishing returns of archaeological crop marks in lowland areas from traditional observer‐
directed visible spectrum aerial survey with standard photographic cameras highlights a …
directed visible spectrum aerial survey with standard photographic cameras highlights a …
A novel strategy of near-infrared spectroscopy dimensionality reduction for discrimination of grades, varieties and origins of green tea
P Liu, Y Wen, J Huang, A Xiong, J Wen, H Li… - Vibrational …, 2019 - Elsevier
Supervised orthogonal locality preserving projection (SOLPP), a supervised manifold
learning dimensionality reduction method, was employed to reduce near-infrared (NIR) …
learning dimensionality reduction method, was employed to reduce near-infrared (NIR) …
[PDF][PDF] Evaluation of land use/land cover classification accuracy using multi-resolution remote sensing images.
Timely and accurate land use/land cover (LULC) information is requisite for sustainable
planning and management of natural resources. Remote sensing images are major …
planning and management of natural resources. Remote sensing images are major …