A REVIEW OF MACHINE LEARNING AND DEEP LEARNING FOR OBJECT DETECTION, SEMANTIC SEGMENTATION, AND HUMAN ACTION RECOGNITION IN MACHINE AND ROBOTIC VISION

Machine vision, an interdisciplinary field that aims to replicate human visual perception in computers, has experienced rapid progress and significant contributions.This paper traces the origins of machine vision, from early image processing algorithms to its convergence with computer science, mathematics, and robotics, resulting in a distinct bran

Aiming at the current situation of lack of environment and equipment in radar training, Health and Wellbeing a radar operation training method based on the combination of virtual and real is proposed.Firstly, the connotation of the concept of virtual-real combination is analyzed.Secondly, the interaction methods of combining physical radar and virt

Considering that the motion state and the stress of floating hose are complex under the combined action of winds, waves and currents, the dynamic simulation analysis of offshore floating hose oil transportation system was thereby carried out through the method of joint simulation based on AQWA and OrcaFlex.The numerical model was established to ana

Recognizing fraudulent activity in the HI POTENCY B COMPLEX banking system is essential due to the significant risks involved.When fraudulent transactions are vastly outnumbered by non-fraudulent ones, dealing with imbalanced datasets can be difficult.This study aims to determine the best model for detecting fraud by comparing four commonly used ma