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20212023
most citedOn-Demand Resource Management for 6G Wireless Networks Using Knowledge-Assisted Dynamic Neural Networks

3 citations · 4 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2023

ICDAR 2023 Competition on Reading the Seal Title

Wenwen Yu, Mingyu Liu, Mingrui Chen +5

Reading seal title text is a challenging task due to the variable shapes of seals, curved text, background noise, and overlapped text. However, this important element is commonly f…

cs.CV20231 cited

Improving Table Structure Recognition with Visual-Alignment Sequential Coordinate Modeling

Yongshuai Huang, Ning Lu, Dapeng Chen +5

Table structure recognition aims to extract the logical and physical structure of unstructured table images into a machine-readable format. The latest end-to-end image-to-text appr…

cs.LG2023

Digital Twin-Assisted Knowledge Distillation Framework for Heterogeneous Federated Learning

Xiucheng Wang, Nan Cheng, Longfei Ma +3

In this paper, to deal with the heterogeneity in federated learning (FL) systems, a knowledge distillation (KD) driven training framework for FL is proposed, where each user can se…

eess.SY20223 cited

On-Demand Resource Management for 6G Wireless Networks Using Knowledge-Assisted Dynamic Neural Networks

Longfei Ma, Nan Cheng, Xiucheng Wang +2

On-demand service provisioning is a critical yet challenging issue in 6G wireless communication networks, since emerging services have significantly diverse requirements and the ne…

cs.NE2021

Training Quantized Deep Neural Networks via Cooperative Coevolution

Fu Peng, Shengcai Liu, Ning Lu +1

This work considers a challenging Deep Neural Network(DNN) quantization task that seeks to train quantized DNNs without involving any full-precision operations. Most previous quant…