An accurate identification of objects from the acquisition system depends on the clear
segmentation and classification of remote sensing images. With the limited financial …

The main goal of this research paper is to apply a deep neural network model for time series
forecasting of environmental variables. Accurate forecasting of snow cover and NDVI are …

In power fingerprint identification, feature information is insufficient when using a single
feature to identify equipment, and small load data of specific customers, difficult to meet the …

Importance Pain is a silent global epidemic impacting approximately a third of the
population. Pharmacological and surgical interventions are primary modes of treatment …

A brain tumor is a lethal neurological disease that affects the average performance of the
brain and can be fatal. In India, around 15 million cases are diagnosed yearly. To mitigate …

An early brain tumor diagnosis is crucial for effective and proactive treatment, which
improves the patient's survival rate. In this paper, we propose a novel Deep Convolutional …

Agriculture is critical for a country's population growth and economic expansion. In Saudi
Arabia (SA), agriculture relies on groundwater, seasonal water, desalinated water, and …

Hyperspectral images can easily discriminate different materials due to their fine spectral
resolution. However, obtaining a hyperspectral image (HSI) with a high spatial resolution is …

Deep Learning (DL) based downscaling has recently become a popular tool in earth
sciences. Multiple DL methods are routinely used to downscale coarse-scale precipitation …

The specific characteristics of remote sensing images, such as large directional variations,
large target sizes, and dense target distributions, make target detection a challenging task …