102 citations · 179 across the 13 of their papers we have counts for
13 papers
Read Pointer Meters in complex environments based on a Human-like Alignment and Recognition Algorithm
Yan Shu, Shaohui Liu, Honglei Xu +1
Recently, developing an automatic reading system for analog measuring instruments has gained increased attention, as it enables the collection of numerous state of equipment. Nonet…
Image Compressed Sensing Using Non-local Neural Network
Wenxue Cui, Shaohui Liu, Feng Jiang +1
Deep network-based image Compressed Sensing (CS) has attracted much attention in recent years. However, the existing deep network-based CS schemes either reconstruct the target ima…
Multi-Stage Residual Hiding for Image-into-Audio Steganography
Wenxue Cui, Shaohui Liu, Feng Jiang +2
The widespread application of audio communication technologies has speeded up audio data flowing across the Internet, which made it a popular carrier for covert communication. In t…
Improving Entity Linking by Modeling Latent Entity Type Information
Shuang Chen, Jinpeng Wang, Feng Jiang +1
Existing state of the art neural entity linking models employ attention-based bag-of-words context model and pre-trained entity embeddings bootstrapped from word embeddings to asse…
Convolutional Neural Networks based Intra Prediction for HEVC
Wenxue Cui, Tao Zhang, Shengping Zhang +3
Traditional intra prediction methods for HEVC rely on using the nearest reference lines for predicting a block, which ignore much richer context between the current block and its n…
Deep neural network based sparse measurement matrix for image compressed sensing
Wenxue Cui, Feng Jiang, Xinwei Gao +2
Gaussian random matrix (GRM) has been widely used to generate linear measurements in compressed sensing (CS) of natural images. However, there actually exist two disadvantages with…
An efficient deep convolutional laplacian pyramid architecture for CS reconstruction at low sampling ratios
Wenxue Cui, Heyao Xu, Xinwei Gao +3
The compressed sensing (CS) has been successfully applied to image compression in the past few years as most image signals are sparse in a certain domain. Several CS reconstruction…
An End-to-End Compression Framework Based on Convolutional Neural Networks
Feng Jiang, Wen Tao, Shaohui Liu +3
Deep learning, e.g., convolutional neural networks (CNNs), has achieved great success in image processing and computer vision especially in high level vision applications such as r…
Single Image Super-Resolution with Dilated Convolution based Multi-Scale Information Learning Inception Module
Wuzhen Shi, Feng Jiang, Debin Zhao
Traditional works have shown that patches in a natural image tend to redundantly recur many times inside the image, both within the same scale, as well as across different scales.…
Deep Networks for Compressed Image Sensing
Wuzhen Shi, Feng Jiang, Shengping Zhang +1
The compressed sensing (CS) theory has been successfully applied to image compression in the past few years as most image signals are sparse in a certain domain. Several CS reconst…
Structural Group Sparse Representation for Image Compressive Sensing Recovery
Jian Zhang, Debin Zhao, Feng Jiang +1
Compressive Sensing (CS) theory shows that a signal can be decoded from many fewer measurements than suggested by the Nyquist sampling theory, when the signal is sparse in some dom…
Spatially Directional Predictive Coding for Block-based Compressive Sensing of Natural Images
Jian Zhang, Debin Zhao, Feng Jiang
A novel coding strategy for block-based compressive sens-ing named spatially directional predictive coding (SDPC) is proposed, which efficiently utilizes the intrinsic spatial cor-…
High Quality Image Interpolation via Local Autoregressive and Nonlocal 3-D Sparse Regularization
Xinwei Gao, Jian Zhang, Feng Jiang +3
In this paper, we propose a novel image interpolation algorithm, which is formulated via combining both the local autoregressive (AR) model and the nonlocal adaptive 3-D sparse mod…