In remote sensing (RS), use of single optical sensors is frequently inadequate for practical
Earth observation applications (eg, agricultural, forest, ecology monitoring) due to trade-offs …

Unmanned Aerial Vehicles (UAVs) play an important role in many applications, including
health, transport, telecommunications and safe and rescue operations. Their adoption can …

Feature extraction from planetary remote sensing images is a primary image processing task
for object recognition, crater counter, morphological structure dimension and unpaired …

In recent years, deep learning-based methods have been extensively developed to
diagnose Prostate Cancer (PCa) with bi-parametric Magnetic Resonance Imaging (bpMRI) …

Causal inference is considered a crucial topic in the medical field, as it enables the
determination of causal effects for medical treatments through data analysis. However, the …

We propose an approach to jointly count plants and detect gaps in maize fields using end-to-
end deep-learning models. Unlike previous efforts that focused solely on plant detection our …

Recently, scene text detection based on pixel-level segmentation becomes quite popular in
industry, which is suitable for real-time digital meter reading detection. However, detection …

Video anomaly detection is a very challenging task in the field of computer vision. In this
paper, we propose a multidimensional two-stage memory-guided network based on future …

Maize is a globally important cereal and fodder crop. Accurate monitoring of maize planting
densities is vital for informed decision-making by agricultural managers. Compared to …

The measurement of target position in dual or multiple unmanned aerial vehicle (UAV)
scenarios presents significant challenges, including data fusion for accurate location and …