This paper presents an automatic content-based image retrieval (CBIR) system for brain tumors on T1-weighted contrast-enhanced magnetic resonance images (CE-MRI).The key challenge in CBIR systems for MR images is the semantic gap between the low-level visual information captured by the MRI machine and the high-level information perceived by the hum
The inception of laboratory work for the construction of a removable, tooth-moving appliance by sectioning teeth from the malocclusion model to align them with wax and achieve minor dental correction has evolved into a state of digital planning and appliance manufacturing for a wide spectrum of malocclusions.The groundbreaking technology of directl
There are still various challenges in remote sensing semantic segmentation due to objects diversity and complexity.Transformer-based models have significant advantages in capturing global feature dependencies for segmentation.However, it unfortunately ignores local feature details.On the other hand, convolutional neural network (CNN), with a differ
The purpose of this study was to model the relationship between the frequency of dust storms and climatic variables in desert areas of Iran.For this purpose, climatic data of temperature (maximum and minimum), rainfall, wind speed (maximum and minimum), and their relationship with the number of days with dust recorded in 25 meteorological stations
Incidental fisheries bycatch is recognised as a major threat to albatross populations worldwide.However, fishery discards and offal produced in large quantities might benefit some scavenging seabirds.Here, we demonstrate an integrated approach to better understand the ecological ramifications of fine-scale overlap between seabirds and fisheries.As