Deep Learning-Based NOMA System for Enhancement of 5G Networks: A Review.

The fresh and rising demands for high-reliability and ultrahigh-capacity wireless communication have led to extensive research into 5G communications. The wide progress in deep learning (DL) and nonorthogonal multiple access (NOMA) technologies provides countless benefits to communication systems. This survey provides the broad scope of DL-based NOMA for the augmentation of 5G networks.

A review on computer-aided recent developments for automatic detection of diabetic retinopathy.

Diabetic retinopathy is a serious microvascular disorder that might result in loss of vision and blindness. It seriously damages the retinal blood vessels and reduces the light-sensitive inner layer of the eye. Due to the manual inspection of retinal fundus images on diabetic retinopathy to detect the morphological abnormalities in Microaneurysms (MAs), Exudates (EXs), Haemorrhages (HMs), and Inter retinal microvascular abnormalities (IRMA) is very difficult and time consuming process.

Volumetric medical image compression using 3D listless embedded block partitioning.

This paper presents a listless variant of a modified three-dimensional (3D)-block coding algorithm suitable for medical image compression. A higher degree of correlation is achieved by using a 3D hybrid transform. The 3D hybrid transform is performed by a wavelet transform in the spatial dimension and a Karhunen-Loueve transform in the spectral dimension.