6 citations · 7 across the 5 of their papers we have counts for
5 papers
L3TC: Leveraging RWKV for Learned Lossless Low-Complexity Text Compression
Junxuan Zhang, Zhengxue Cheng, Yan Zhao +4
Learning-based probabilistic models can be combined with an entropy coder for data compression. However, due to the high complexity of learning-based models, their practical applic…
Beyond Feature Mapping GAP: Integrating Real HDRTV Priors for Superior SDRTV-to-HDRTV Conversion
Gang He, Kepeng Xu, Li Xu +3
The rise of HDR-WCG display devices has highlighted the need to convert SDRTV to HDRTV, as most video sources are still in SDR. Existing methods primarily focus on designing neural…
OmniDataComposer: A Unified Data Structure for Multimodal Data Fusion and Infinite Data Generation
Dongyang Yu, Shihao Wang, Yuan Fang +1
This paper presents OmniDataComposer, an innovative approach for multimodal data fusion and unlimited data generation with an intent to refine and uncomplicate interplay among dive…
CNN-MERP: An FPGA-Based Memory-Efficient Reconfigurable Processor for Forward and Backward Propagation of Convolutional Neural Networks
Xushen Han, Dajiang Zhou, Shihao Wang +1
Large-scale deep convolutional neural networks (CNNs) are widely used in machine learning applications. While CNNs involve huge complexity, VLSI (ASIC and FPGA) chips that deliver…
Chain-NN: An Energy-Efficient 1D Chain Architecture for Accelerating Deep Convolutional Neural Networks
Shihao Wang, Dajiang Zhou, Xushen Han +1
Deep convolutional neural networks (CNN) have shown their good performances in many computer vision tasks. However, the high computational complexity of CNN involves a huge amount…