Tri-level Combination for Image Representation

2016 ◽  
pp. 250-259
Author(s):  
Ruiying Li ◽  
Chunjie Zhang ◽  
Qingming Huang
Keyword(s):  
Image Representation

Convolutional Dictionary Pair Learning Network for Image Representation Learning.pdf

2019 ◽  
Author(s):  
Zhao Zhang ◽  
Yulin Sun ◽  
Yang Wang ◽  
Zhengjun Zha ◽  
Shuicheng Yan ◽  
...  
Keyword(s):  
Image Representation ◽  
Learning Network

10 pages, 6 figures

Image Representation Using Bag-of-phrases

2012 ◽  
Vol 38 (1) ◽  
pp. 46-54 ◽  
Author(s):  
Lin-Bo ZHANG ◽  
Chun-Heng WANG ◽  
Bai-Hua XIAO ◽  
Yun-Xue SHAO
Keyword(s):  
Image Representation

scholarly journals An improved novel quantum image representation and its experimental test on IBM quantum experience

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jie Su ◽  
Xuchao Guo ◽  
Chengqi Liu ◽  
Shuhan Lu ◽  
Lin Li
Keyword(s):  
Image Processing ◽  
Information Processing ◽  
Quantum Information ◽  
Quantum Information Processing ◽  
Image Representation ◽  
Reference Value ◽  
Vertical Position ◽  
Quantum Image ◽  
Quantum Image Representation ◽  
Ibm Quantum Experience

AbstractQuantum image representation (QIR) is a necessary part of quantum image processing (QIP) and plays an important role in quantum information processing. To address the problems that NCQI cannot handle images with inconsistent horizontal and vertical position sizes and multi-channel image processing, an improved color digital image quantum representation (INCQI) model based on NCQI is proposed in this paper. The INCQI model can process color images and facilitate multi-channel quantum image transformations and transparency information processing of images using auxiliary quantum bits. In addition, the quantum image control circuit was designed based on INCQI. And quantum image preparation experiments were conducted on IBM Quantum Experience (IBMQ) to verify the feasibility and effectiveness of INCQI quantum image preparation. The prepared image information was obtained by quantum measurement in the experiment, and the visualization of quantum information was successfully realized. The research in this paper has some reference value for the research related to QIP.

Image Representation Learning by Transformation Regression

2021 ◽  
Author(s):  
Xifeng Guo ◽  
Jiyuan Liu ◽  
Sihang Zhou ◽  
En Zhu ◽  
Shihao Dong
Keyword(s):  
Image Representation ◽  
Representation Learning

scholarly journals Fine-Tuning and Training of DenseNet for Histopathology Image Representation Using TCGA Diagnostic Slides

2021 ◽  
pp. 102032
Author(s):  
Abtin Riasatian ◽  
Morteza Babaie ◽  
Danial Maleki ◽  
Shivam Kalra ◽  
Mojtaba Valipour ◽  
...  
Keyword(s):  
Image Representation ◽  
Fine Tuning ◽  
And Training
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