Hardware, low power consumption, high accuracy and performance are crucial factors for
deep learning applications. High level graphics processing units (GPU) are commonly used …

Simultaneous localization and map** (SLAM) is an active research topic in machine
vision and robotics. It has various applications in many different fields such as mobile robots …

Deep Learning (DL) has become a topic of study in various applications, including
healthcare. The important factors considered in building a deep learning model are …

In the past decade, Internet of Things (IoT) technology has been widely used in various
applications in daily life. Currently, IoT applications primarily depend on powerful cloud data …

Several works have focused on Simultaneous Localization and Map** (SLAM), which is a
topic that has been studied for more than a decade to meet the needs of robots to navigate …

In recent years, multi-robot control systems and service robots equipped with graphical
computing have been introduced in various application scenarios. However, the long-term …

Real-time semantic segmentation on embedded devices has recently enjoyed significant
gain in popularity, due to the increasing interest in smart vehicles and smart robots. In …

Increasing awareness of the importance of head personal protective equipment in industrial
and construction environments has become a major concern in efforts to improve …

Loop Closure (LC) is a crucial task in Simultaneous Localization and Map** (SLAM) for
Autonomous Ground Vehicles (AGV). It is an active research area because it improves …

Visual odometry plays a crucial role in addressing the challenge of relative localization for
autonomous vehicles. However, achieving rapid and accurate pose estimation in complex …