Results 221 to 230 of about 2,163,711 (277)

Variational Deep Alliance: A Generative Auto-Encoding Approach to Longitudinal Data Analysis. [PDF]

Entropy (Basel)
Feng S, Xie W, Nie Y.
europepmc   +1 more source

Interpretable nonconvex submodule clustering algorithm using ℓr-induced tensor nuclear norm and ℓ2,p column sparse norm with global convergence guarantees. [PDF]

PLoS One
Yang M, Han S, Chen L, Wang J.
europepmc   +1 more source

A High-Fidelity Framework for 3D Dental Crown Reconstruction Using Intraoral Images. [PDF]

Int Dent J
Liao N, Zhang X, Chen W, Zhang X, Mo S.
europepmc   +1 more source

Breast cancer histopathological image classification based on collaborative multi-domain feature learning. [PDF]

PLoS One
He L, Hu H, Cheng R.
europepmc   +1 more source

Multi-Frequency GPR Image Fusion Based on Convolutional Sparse Representation to Enhance Road Detection. [PDF]

J Imaging
Fang L, Yang F, Fang Y, Nie J.
europepmc   +1 more source

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Improved image representation and sparse representation for image classification

Applied Intelligence, 2020
It seems that for multiple available images of the same object, the pixel values at the same image position are almost always different, which is especially obvious for the deformable object. This implies that it will be not easy to correctly classify the deformable object.
Shijun Zheng, Yongjun Zhang, Wenjie Liu, Yongjie Zou   +3 more
openaire   +1 more source

Holographic representations of images

IEEE Transactions on Image Processing, 1998
We discuss a new type of holographic image representations that have advantages in a "distributed" world. We call these representations holographic. Arbitrary portions of a holographic representation enable reconstruction of the whole image, with distortions that decrease gradually with the increase in the size of the portions available.
A M, Bruckstein, R J, Holt, A N, Netravali   +2 more
openaire   +2 more sources

Nonredundant image representations

Proceedings of International Conference on Image Processing, 2002
We consider the problem of sending raw image data over lossy or heterogeneous network connections with as little overhead as possible. If the network connection does not support multiple priority levels and the network drops packets at random, a technique is needed where the data would be divided into parts of equal importance, so that the image could ...
F.M.L. Ng, J. Kovacevic
openaire   +1 more source

Quantum Image Representations

2020
In this chapter, mainstream QIRs are reviewed and classified into three models based on different requirements to capture the content of an image. They are thoroughly compared in terms of their color information encoding strategies, computational complexities of preparation, and measurement-based retrievals.
Fei Yan, Salvador E. Venegas-Andraca
openaire   +1 more source

Multilayered image representation: application to image compression

IEEE Transactions on Image Processing, 2002
The main contribution of this work is a new paradigm for image representation and image compression. We describe a new multilayered representation technique for images. An image is parsed into a superposition of coherent layers: piecewise smooth regions layer, textures layer, etc.
François G, Meyer, Amir Z, Averbuch, Ronald R, Coifman   +2 more
openaire   +2 more sources