Zobrazeno 1 - 10
of 158
pro vyhledávání: '"Li, Yangyan"'
Autor:
Li, Yangyang
Titanium is one of the earth-abundant elements, and its oxides including titanium dioxide (TiO2) and strontium titanium oxide (SrTiO3) are widely used in technologies of electronics, energy conversion, catalysis, sensing, and so on. Generally, the Ti
Externí odkaz:
http://hdl.handle.net/10754/621827
Thesis: M. Eng. in Advanced Manufacturing and Design, Massachusetts Institute of Technology, Department of Mechanical Engineering, September, 2018
Cataloged from the PDF version of thesis.
Includes bibliographical references (pages 43-44).<
Cataloged from the PDF version of thesis.
Includes bibliographical references (pages 43-44).<
Externí odkaz:
https://hdl.handle.net/1721.1/132738
Autor:
Li, Yangyang
The (BMN) bulk materials were sintered at 1050°C, 1100°C, 1150°C, 1200°C by the conventional ceramic process, and their microstructure and dielectric properties were investigated by Scanning electron microscopy (SEM), X-ray diffraction (XRD), Ram
Externí odkaz:
http://hdl.handle.net/10754/293689
Autor:
Li, Yangyang
We present a vision for 4G cellular networks based on the concept of autonomous infrastructure deployment. Cellular base stations, or femtocell access points, are deployed by network users without being constrained by the conventional cell planning p
Externí odkaz:
http://hdl.handle.net/1807/24815
Photographing optoelectronic displays often introduces unwanted moir\'e patterns due to analog signal interference between the pixel grids of the display and the camera sensor arrays. This work identifies two problems that are largely ignored by exis
Externí odkaz:
http://arxiv.org/abs/2404.18155
We study how choices of input point cloud coordinate frames impact learning of manipulation skills from 3D point clouds. There exist a variety of coordinate frame choices to normalize captured robot-object-interaction point clouds. We find that diffe
Externí odkaz:
http://arxiv.org/abs/2210.07442
RGB-D semantic segmentation has attracted increasing attention over the past few years. Existing methods mostly employ homogeneous convolution operators to consume the RGB and depth features, ignoring their intrinsic differences. In fact, the RGB val
Externí odkaz:
http://arxiv.org/abs/2108.10528
Autor:
Cao, Jinming, Li, Yangyan, Sun, Mingchao, Chen, Ying, Lischinski, Dani, Cohen-Or, Daniel, Chen, Baoquan, Tu, Changhe
Convolutional layers are the core building blocks of Convolutional Neural Networks (CNNs). In this paper, we propose to augment a convolutional layer with an additional depthwise convolution, where each input channel is convolved with a different 2D
Externí odkaz:
http://arxiv.org/abs/2006.12030
Existing CNN-based methods for pixel labeling heavily depend on multi-scale features to meet the requirements of both semantic comprehension and detail preservation. State-of-the-art pixel labeling neural networks widely exploit conventional scale-tr
Externí odkaz:
http://arxiv.org/abs/2005.13363
Learning disentangled representations of data is a fundamental problem in artificial intelligence. Specifically, disentangled latent representations allow generative models to control and compose the disentangled factors in the synthesis process. Cur
Externí odkaz:
http://arxiv.org/abs/2005.07728