This paper is an overview to Visual Simultaneous Localization and Mapping (V-SLAM). We
discuss the basic definitions in the SLAM and vision system fields and provide a review of …

Autonomous localization and navigation, as an essential research area in robotics, has a
broad scope of applications in various scenarios. To widen the utilization environment and …

Among the world's most common cancers, colorectal cancer is the third most severe form of
cancer. Early polyp detection reduces the risk of colorectal cancer, vital for effective …

In the field of building detection research, an accurate, state-of-the-art semantic
segmentation model must be constructed to classify each pixel of the image, which has an …

Abstract Thispaper presents a Neural Network aimed at robust and fast visual loop detection
in underwater environments. The proposal is based on an autoencoder architecture, in …

We introduce NeuV-SLAM, a novel dense simultaneous localization and mapping pipeline
based on neural multiresolution voxels, characterized by ultra-fast convergence and …

Classification of seat occupancy in in-vehicle interior remains a significant challenge and is
a promising area in the functionality of new generation cars. As majority of accidents are …

In recent years, AI and deep learning (DL) methods have been widely used for object
classification, recognition, and segmentation of high-resolution multispectral remote sensing …

Visual simultaneous localization and mapping (VSLAM) enhances the navigation of
autonomous agents in unfamiliar environments by progressively constructing maps and …

In clinical diagnosis and surgical planning, extracting brain tumors from magnetic resonance
images (MRI) is very important. Nevertheless, considering the high variability and imbalance …