Hongmei Zhu's research while affiliated with Beihang University (BUAA) and other places
What is this page?
This page lists the scientific contributions of an author, who either does not have a ResearchGate profile, or has not yet added these contributions to their profile.
It was automatically created by ResearchGate to create a record of this author's body of work. We create such pages to advance our goal of creating and maintaining the most comprehensive scientific repository possible. In doing so, we process publicly available (personal) data relating to the author as a member of the scientific community.
If you're a ResearchGate member, you can follow this page to keep up with this author's work.
If you are this author, and you don't want us to display this page anymore, please let us know.
It was automatically created by ResearchGate to create a record of this author's body of work. We create such pages to advance our goal of creating and maintaining the most comprehensive scientific repository possible. In doing so, we process publicly available (personal) data relating to the author as a member of the scientific community.
If you're a ResearchGate member, you can follow this page to keep up with this author's work.
If you are this author, and you don't want us to display this page anymore, please let us know.
Publications (9)
In this letter, an alternative data-driven HSI classification model based on CapsNet is proposed rather than recently predominant convolutional neural network (CNN)-based models. To adjust the CapsNet to HSI classification, we tune a new CapsNet architecture with three convolutional layers. The added shallow layer provides higher level features to...
Stereo matching between binocular stereo images is fundamental to many computer vision tasks, such as threedimensional (3D) reconstruction and robot navigation. Various structures of real 3D scenes lead stereo matching to be an old yet still challenging problem. In this study, the authors proposed a novel adaptive support weights technique which ex...
We propose a novel data-driven matching cost for dense correspondence based on sparse theory. The ability of sparse coding to selectively express the sources of influence on stereo images allows us to learn a discriminative dictionary. The dictionary learning process is incorporated with discriminative learning and weighted sparse coding to enhance...
Citations
... Thus, when the liver image is recognized using the CNN model, the overlapping of the images between the organs causes the deterioration of the learning feature's effect, thereby affecting recognition accuracy. As a new framework for deep learning, CapsNet [15][16][17][18][19][20][21][22] encompasses many of the advantages of the CNN model. As CapsNet converts the scalar output of neurons into a vector output, the spatial relationship between liver tumor features can be well established by calculating the probability of the length and direction of the output vector. ...
![[object Object]](https://i1.rgstatic.net/ii/profile.image/1067872516337664-1631612056242_Q64/Sen-Li-53.jpg)
... To solve these problems, traditional solutions include global-based algorithms and localbased algorithms. Local-based algorithms mainly concentrate on how to find perfect support windows that guarantee all the pixels within each window have the same or similar disparities [55]. The major challenge is to find a well-suited size for the support window [15]. ...
... Global stereo matching algorithms require computationally demanding optimization algorithms, such as graph cuts [2] and dynamic programming [3,4], to find the disparity of each pixel. To facilitate the algorithms in real time, [5] implemented an integrated scheme combining a dynamic programming algorithm and a local algorithm using a graphics processing unit (GPU), while [6] implemented semi-global stereo matching using a field-programmable gate array (FPGA). ...
... Low grazing and shadows appear as low backscatter areas. Shadow estimation algorithms using DEM for RADAR images is described in (Prasath and Haddad 2013;Zhu et al. 2016). A slightly modified approach using trigonometric computation, optimized for segment-based processing is used. ...
... When the depth map is available, a pixel neighbor is useful for this task since we know the correspondence between a pixel and its reprojected 3D point. In summary, the computational cost might be unexpectedly changed depending on the input data, but this is not a significant problem since there are some algorithms supporting the fast calculation of normal vectors (e.g., [18,19]). ...
![[object Object]](https://i1.rgstatic.net/ii/profile.image/279976751452163-1443763067255_Q64/Zhao-Hongwei-2.jpg)
