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18 papers · 2 filters
SFCN-OPI: Detection and Fine-grained Classification of Nuclei Using Sibling FCN with Objectness Prior Interaction
Yanning Zhou, Qi Dou, Hao Chen +2
Cell nuclei detection and fine-grained classification have been fundamental yet challenging problems in histopathology image analysis. Due to the nuclei tiny size, significant inte…
Learning a Wavelet-like Auto-Encoder to Accelerate Deep Neural Networks
Tianshui Chen, Liang Lin, Wangmeng Zuo +2
Accelerating deep neural networks (DNNs) has been attracting increasing attention as it can benefit a wide range of applications, e.g., enabling mobile systems with limited computi…
Image Super-resolution via Feature-augmented Random Forest
Hailiang Li, Kin-Man Lam, Miaohui Wang
Recent random-forest (RF)-based image super-resolution approaches inherit some properties from dictionary-learning-based algorithms, but the effectiveness of the properties in RF i…
Learning a Single Convolutional Super-Resolution Network for Multiple Degradations
Kai Zhang, Wangmeng Zuo, Lei Zhang
Recent years have witnessed the unprecedented success of deep convolutional neural networks (CNNs) in single image super-resolution (SISR). However, existing CNN-based SISR methods…
Direction-aware Spatial Context Features for Shadow Detection
Xiaowei Hu, Lei Zhu, Chi-Wing Fu +2
Shadow detection is a fundamental and challenging task, since it requires an understanding of global image semantics and there are various backgrounds around shadows. This paper pr…
Learning Aggregated Transmission Propagation Networks for Haze Removal and Beyond
Risheng Liu, Xin Fan, Minjun Hou +3
Single image dehazing is an important low-level vision task with many applications. Early researches have investigated different kinds of visual priors to address this problem. How…