Residual Networks of Residual Networks: Multilevel Residual Networks
نویسندگان
چکیده
منابع مشابه
Residual Networks of Residual Networks: Multilevel Residual Networks
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...
متن کاملResidual closeness in networks
A new characteristic (residual closeness) which can measure the network resistance is presented. It evaluates closeness after removal of vertices or links, hence two types are considered—vertices and links residual closeness. This characteristic is more sensitive than the well-known measures of vulnerability—it captures the result of actions even if they are small enough not to disconnect the g...
متن کاملVisualizing Residual Networks
Residual networks are the current state of the art on ImageNet. Similar work in the direction of utilizing shortcut connections has been done extremely recently with derivatives of residual networks and with highway networks. This work potentially challenges our understanding that CNNs learn layers of local features that are followed by increasingly global features. Through qualitative visualiz...
متن کاملBoosted Residual Networks
In this paper we present a new ensemble method, called Boosted Residual Networks, which builds an ensemble of Residual Networks by growing the member network at each round of boosting. The proposed approach combines recent developements in Residual Networks a method for creating very deep networks by including a shortcut layer between different groups of layers with the Deep Incremental Boostin...
متن کاملTernary Residual Networks
Sub-8-bit representation of DNNs incur some discernible loss of accuracy despite rigorous (re)training at low-precision. Such loss of accuracy essentially makes them equivalent to a much shallower counterpart, diminishing the power of being deep networks. To address this problem of accuracy drop we introduce the notion of residual networks where we add more low-precision edges to sensitive bran...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Circuits and Systems for Video Technology
سال: 2018
ISSN: 1051-8215,1558-2205
DOI: 10.1109/tcsvt.2017.2654543