Recent advances in crop disease detection using UAV and deep learning techniques
Because of the recent advances in drones or Unmanned Aerial Vehicle (UAV) platforms,
sensors and software, UAVs have gained popularity among precision agriculture …
sensors and software, UAVs have gained popularity among precision agriculture …
Explanatory classification of CXR images into COVID-19, Pneumonia and Tuberculosis using deep learning and XAI
Chest X-ray (CXR) images are considered useful to monitor and investigate a variety of
pulmonary disorders such as COVID-19, Pneumonia, and Tuberculosis (TB). With recent …
pulmonary disorders such as COVID-19, Pneumonia, and Tuberculosis (TB). With recent …
Fruit classification using attention-based MobileNetV2 for industrial applications
Recent deep learning methods for fruits classification resulted in promising performance.
However, these methods are with heavy-weight architectures in nature, and hence require a …
However, these methods are with heavy-weight architectures in nature, and hence require a …
Deep Learning‐Based Methods for Sentiment Analysis on Nepali COVID‐19‐Related Tweets
COVID‐19 has claimed several human lives to this date. People are dying not only because
of physical infection of the virus but also because of mental illness, which is linked to …
of physical infection of the virus but also because of mental illness, which is linked to …
CNN-LSTM vs. LSTM-CNN to predict power flow direction: a case study of the high-voltage subnet of northeast Germany
The massive installation of renewable energy sources together with energy storage in the
power grid can lead to fluctuating energy consumption when there is a bi-directional power …
power grid can lead to fluctuating energy consumption when there is a bi-directional power …
[HTML][HTML] Fusing Landsat 8 and Sentinel-2 data for 10-m dense time-series imagery using a degradation-term constrained deep network
Dense medium-resolution imagery is essential for fine-scale time-series applications. The
combined use of Landsat 8 and Sentinel-2 can derive 10-m time-series imagery at a …
combined use of Landsat 8 and Sentinel-2 can derive 10-m time-series imagery at a …
Methods in the spatial deep learning: Current status and future direction
A deep neural network (DNN), evolved from a traditional artificial neural network, has been
seamlessly adapted for the spatial data domain over the years. Deep learning (DL) has …
seamlessly adapted for the spatial data domain over the years. Deep learning (DL) has …
Forest fire pattern and vulnerability mapping using deep learning in Nepal
Background In the last two decades, Nepal has experienced an increase in both forest fire
frequency and area, but very little is known about its spatiotemporal dimension. A limited …
frequency and area, but very little is known about its spatiotemporal dimension. A limited …
Classification of Citrus huanglongbing degree based on cbam-mobilenetv2 and transfer learning
S Dou, L Wang, D Fan, L Miao, J Yan, H He - Sensors, 2023 - mdpi.com
Citrus has become a pivotal industry for the rapid development of agriculture and increasing
farmers' incomes in the main production areas of southern China. Knowing how to diagnose …
farmers' incomes in the main production areas of southern China. Knowing how to diagnose …
A cooperative scheme for late leaf spot estimation in peanut using UAV multispectral images
In Australia, peanuts are mainly grown in Queensland with tropical and subtropical climates.
The most common foliar disease that poses a severe threat to quality peanut production is …
The most common foliar disease that poses a severe threat to quality peanut production is …