Single-image rain removal always was one of the difficulties in environment perception task. Usually, it has two paths to solve this problem: data-driven solutions and model-based solutions. Due benefits convenient, learning features automatically rapidly, data driven attracted tremendous interests. However, time consumed per frame is still hard match requirement high real-time performance, esp...

Colorectal cancer is a dangerous disease with high mortality rate. To increase the likelihood of successful treatment, early detection polyps useful solution. The Unet-architecture network model showing success in medical image segmentation including analysis from colonoscopy images. Traditional Unet and Unet-based models are often huge, requiring training deployment high-performance system. De...

A residual-networks family with hundreds or even thousands of layers dominates major image recognition tasks, but building a network by simply stacking residual blocks inevitably limits its optimization ability. This paper proposes a novel residual-network architecture, Residual networks of Residual networks (RoR), to dig the optimization ability of residual networks. RoR substitutes optimizing...

The article presents an approach to the maximum flow problem in parametric networks with linear capacity functions of a single parameter, based on the concept of shortest conditional augmenting directed path. In order to avoid working with piecewise linear functions, our approach uses a series of parametric residual networks defined for successive subintervals of the parameter values where the ...

This report addresses the design of distributed medium access control (MAC) protocols for wireless sensor networks under the performance measure of network lifetime. Integrated in the design of MAC schemes are two key physical layer parameters: the channel state and the residual energy of each sensor. The impact of incorporating these parameters in MAC design on network lifetime is studied. Fur...