Point Cloud Quality Assessment Using a One-Dimensional Model Based on the Convolutional Neural Network.

Recent advancements in 3D modeling have revolutionized various fields, including virtual reality, computer-aided diagnosis, and architectural design, emphasizing the importance of accurate quality assessment for 3D point clouds. As these models undergo operations such as simplification and compression, introducing distortions can significantly impact their visual quality. There is a growing need for reliable and efficient objective quality evaluation methods to address this challenge.

Comparison of Graph Distance Measures for Movie Similarity Using a Multilayer Network Model.

Graph distance measures have emerged as an effective tool for evaluating the similarity or dissimilarity between graphs. Recently, there has been a growing trend in the application of movie networks to analyze and understand movie stories. Previous studies focused on computing the distance between individual characters in narratives and identifying the most important ones.

A Convolutional Neural Network-Based Connectivity Enhancement Approach for Autism Spectrum Disorder Detection.

Autism spectrum disorder (ASD) represents an ongoing obstacle facing many researchers to achieving early diagnosis with high accuracy. To advance developments in ASD detection, the corroboration of findings presented in the existing body of autism-based literature is of high importance. Previous works put forward theories of under- and over-connectivity deficits in the autistic brain.

A discriminative shape-texture convolutional neural network for early diagnosis of knee osteoarthritis from X-ray images.

Knee Osteoarthritis (OA) is one of the most common causes of physical disability worldwide associated with a significant personal and socioeconomic burden. Deep Learning approaches based on Convolutional Neural Networks (CNNs) achieved remarkable improvements in knee OA detection. Despite this success, the problem of early knee OA diagnosis from plain radiographs remains a challenging task.

Diversity and Antimicrobial Activities of Isolated from Mining Soils in Midelt Region, Morocco.

Multidrug-resistant bacteria have emerged as a serious global health threat that requires, more than ever before, an urgent need for novel and more effective drugs. In this regard, the present study sheds light on the diversity and antimicrobial potential of isolates in mining ecosystems. We have indeed investigated the production of bioactive molecules by the isolated from abandoned mining areas in Midelt, Morocco, where average contents of lead (Pb) and cadmium (Cd) are higher than normal world levels.