Residual GRU
A Residual GRU is a gated recurrent unit (GRU) that incorporates the idea of residual connections from ResNets.
Full Resolution Image Compression with Recurrent Neural Networks
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Image Compression is an application of data compression for digital images to lower their storage and/or transmission requirements.
Source: Variable Rate Deep Image Compression With a Conditional Autoencoder
관련 논문에서 소개한 기법입니다. 이 태스크에서의 평가 여부는 평가 결과에서 확인하세요.
A Residual GRU is a gated recurrent unit (GRU) that incorporates the idea of residual connections from ResNets.
Full Resolution Image Compression with Recurrent Neural Networks
Variational Quantum Singular Value Decomposition is a variational quantum algorithm for singular value decomposition (VQSVD). By exploiting the variational principles for singular values and the Ky Fan Theorem, a novel loss function is designed such that two quantum neural networks (or parameterized quantum circuits) could be trained to learn the singular vectors and output the corresponding singular values.
Weighted Recurrent Quality Enhancement, or WRQE, is a recurrent quality enhancement network for video compression that takes both compressed frames and the bit stream as inputs. In the recurrent cell of WRQE, the memory and update signal are weighted by quality features to reasonably leverage multi-frame information for enhancement.
Learning for Video Compression with Hierarchical Quality and Recurrent Enhancement
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