Spectrum sensing is one of the essential tasks to have a cognitive radio system, which will
allow an unlicensed user, called secondary user, to utilize the spectrum while the licensed …

Deep learning for automated lesion detection in mammography has gained widespread
attention due to its potential to reduce the time needed for radiologists to detect lesions …

The usage of deep trends for scientific photograph segmentation has seen a speedy
increase in recognition in recent years of today's capability to generate accurate photo …

Spectrum sensing is of crucial importance in cognitive radio (CR) networks. In this paper, a
reliable spectrum sensing scheme is proposed, which uses K‐nearest neighbor, a machine …

Abstract A Cognitive Radio Sensor Network (CRSN) is a distributed network of sensor
nodes, which senses event signals and collaboratively communicates over dynamically …

Abstract In Orthogonal Frequency Division Multiplexing OFDM, a cyclic prefix (CP) is applied
to reduce the intervention between symbols. The CP results in bandwidth wastage, and the …

The cyclostationary spectrum (CS) method is one of the best at what it does because it
effectively detects idle spectrum with low signal-to-noise ratios (SNR). In order to distinguish …

Currently, the 4G network service has caused massive digital growth in high use. Video
calling has become the go-to Internet application for many people, downloading even huge …

The segmentation accuracy of brain tumors has been improved through the application of
deep learning. According to current research, deep learning may produce high-quality …

Spectrum efficiency decay due to high demand for high data rate and growing technologies,
tens of billions of connected devices need to provide by the services wirelessly causing a …