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Yanbo Gao

Researcher at University of Electronic Science and Technology of China

Publications -  38
Citations -  1057

Yanbo Gao is an academic researcher from University of Electronic Science and Technology of China. The author has contributed to research in topics: Recurrent neural network & Computer science. The author has an hindex of 9, co-authored 29 publications receiving 598 citations. Previous affiliations of Yanbo Gao include Shandong University.

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Proceedings ArticleDOI

Independently Recurrent Neural Network (IndRNN): Building A Longer and Deeper RNN

TL;DR: Independently Recurrent Neural Network (IndRNN) as discussed by the authors is a new type of RNN, where neurons in the same layer are independent of each other and they are connected across layers.
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Independently Recurrent Neural Network (IndRNN): Building A Longer and Deeper RNN

TL;DR: Independently Recurrent Neural Network (IndRNN) as mentioned in this paper is a new type of RNN, where neurons in the same layer are independent of each other and they are connected across layers.
Journal ArticleDOI

Lagrangian Multiplier Adaptation for Rate-Distortion Optimization With Inter-Frame Dependency

TL;DR: This paper investigates RDO with inter-frame dependency, where the impact of coding performance of the current CU on that of the following frames is considered and an RDO scheme taking the inter- frame dependency into account is proposed by adapting the Lagrangian multiplier.
Journal ArticleDOI

Temporally Dependent Rate-Distortion Optimization for Low-Delay Hierarchical Video Coding

TL;DR: A hierarchical temporally dependent RDO scheme is developed specifically for the LD-HCS based on a source distortion propagation model and can achieve higher coding gains, coupled with QP adaption.
Journal ArticleDOI

Optimal Bit Allocation at Frame Level for Rate Control in HEVC

TL;DR: An effective frame level bit allocation method to improve the R-D performance whilst maintaining the high accuracy of the bitrate control in HEVC is proposed and experimental results demonstrate that the proposed method can achieve considerable R- D performance improvement and accurate bit rate control.