Moving object detection from aerial images remains an unsolved problem in computer vision research domain. Detection results are not precise due to blurry images, thin edges and noise. Various methods were previously proposed for moving which could provide robust many challenges, i.e., noise, motion detection, lack of appropriate features, effective classification approach, complex background v...

Abstract It is an important task to estimate a 3D bounding box from monocular images for autonomous driving. However, the pictures do not have distance information, so it difficult acquire accurate results. For sake of solving trouble low accuracy image in target detection because lacking improved three-dimensional algorithm based on GUPNet and neural network was proposed promote precision dete...

Object Detection is one of the most popular applications in branch computer vision. While accuracy has always been focus, focus gradually also shifted to lightweight models. In this paper we propose a light weight system where object classification not required but only detection using clustering methods.

analysis and design of object oriented is onemodern paradigms for developing a system. in this paradigm, there are several objects and each object plays some specific roles. identifying objects (and classes) is one of the most important steps in the object-oriented paradigm. this paper makes a literature review over techniques to identify objects and then presents six taxonomies for them. the f...

There have been many researches on object grasping in cooperating systems assuming no object slippage and stable grasp and the control system is designed to keep the contact force inside the friction cone to prevent the slippage. However undesired slippage can occur due to environmental conditions and many other reasons. In this research, dynamic analysis and control synthesis of a cooperating ...