Manifold learning has attracted more and more attention in machine learning for past decades. Unsupervised Large Graph Embedding (ULGE), which performs well on the large-scale data, has been proposed for manifold lear...
详细信息
In recent years, cloud computing has emerged as an enabling technology, in which virtual machine migration and dynamic resource allocation is one of the hot issues. During the migration of virtual machine, access requ...
详细信息
In order to obtain the stable background of a traffic surveillance video, the application scenarios, computational complexity, and results of the Gaussian background model were analyzed. In the background modeling pro...
详细信息
Ant colony optimization (ACO for short) has been proved a successful meta-heuristic by a huge of empirical studies. This paper discusses the termination criteria of ACO and therefore provides research ideas to other m...
详细信息
To facilitate scene understanding and robot navigation in large scale urban environment, a two-layer enhanced geometric map(EGMap) is designed using videos from a monocular onboard camera. The 2D layer of EGMap consis...
详细信息
To facilitate scene understanding and robot navigation in large scale urban environment, a two-layer enhanced geometric map(EGMap) is designed using videos from a monocular onboard camera. The 2D layer of EGMap consists of a 2D building boundary map from top-down view and a 2D road map, which can support localization and advanced map-matching when compared with standard polyline-based maps. The 3D layer includes features such as 3D road model,and building facades with coplanar 3D vertical and horizontal line segments, which can provide the 3D metric features to localize the vehicles and flying-robots in 3D space. Starting from the 2D building boundary and road map, EGMap is initially constructed using feature fusion with geometric constraints under a line feature-based simultaneous localization and mapping(SLAM) framework iteratively and progressively. Then, a local bundle adjustment algorithm is proposed to jointly refine the camera localizations and EGMap features. Furthermore, the issues of uncertainty, memory use, time efficiency and obstacle effect in EGMap construction are discussed and analyzed. Physical experiments show that EGMap can be successfully constructed in large scale urban environment and the construction method is demonstrated to be very accurate and robust.
Purpose:As to January 11,2021,coronavirus disease(COVID-19)has caused more than 2 million deaths *** diagnostic methods of COVID-19 are:(i)nucleic acid *** method requires high requirements on the sample testing *** c...
详细信息
Purpose:As to January 11,2021,coronavirus disease(COVID-19)has caused more than 2 million deaths *** diagnostic methods of COVID-19 are:(i)nucleic acid *** method requires high requirements on the sample testing *** collecting samples,staff are in a susceptible environment,which increases the risk of infection.(ii)chest computed *** cost of it is high and some radiation in the scan process.(iii)chest X-ray *** has the advantages of fast imaging,higher spatial recognition than chest computed ***,our team chose the chest X-ray images as the experimental dataset in this ***:We proposed a novel framework—BEVGG and three methods(BEVGGC-I,BEVGGC-II,and BEVGGC-III)to diagnose COVID-19 via chest X-ray ***,we used biogeography-based optimization to optimize the values of hyperparameters of the convolutional neural ***:The experimental results show that the OA of our proposed three methods are 97.65%±0.65%,94.49%±0.22%and 94.81%±0.52%.BEVGGC-I has the best performance of all ***:The OA of BEVGGC-I is 9.59%±1.04%higher than that of state-of-the-art methods.
Mobile grid computing is a new computing paradigm which joins classic grid computing and mobile computing paradigm to provide dependable, seamless, pervasive access to mobile resources and services. It can use the und...
详细信息
Mobile grid computing is a new computing paradigm which joins classic grid computing and mobile computing paradigm to provide dependable, seamless, pervasive access to mobile resources and services. It can use the und...
详细信息
With the development of image restoration technology based on deep learning,more complex problems are being solved,especially in image semantic inpainting based on ***,image semantic inpainting techniques are becoming...
详细信息
With the development of image restoration technology based on deep learning,more complex problems are being solved,especially in image semantic inpainting based on ***,image semantic inpainting techniques are becoming more ***,due to the limitations of memory,the instability of training,and the lack of sample diversity,the results of image restoration are still encountering difficult problems,such as repairing the content of glitches which cannot be well integrated with the original ***,we propose an image inpainting network based on Wasserstein generative adversarial network(WGAN)*** the corresponding technology having been adjusted and improved,we attempted to use the Adam algorithm to replace the traditional stochastic gradient descent,and another algorithm to optimize the training used in recent *** evaluated our algorithm on the ImageNet *** obtained high-quality restoration results,indicating that our algorithm improves the clarity and consistency of the image.
With the proliferation of the GPS-enabled devices and mobile techniques, there has been a lot of work on trajectory search in the last decade. Previous trajectory search has focused on spatio-temporal features and tex...
详细信息
暂无评论