activity
20152022
most citedImplementation of Training Convolutional Neural Networks

125 citations · 393 across the 15 of their papers we have counts for

collaborators

15 papers

eess.SP2022★ 116 cited

An Adaptive and Robust Deep Learning Framework for THz Ultra-Massive MIMO Channel Estimation

Wentao Yu, Yifei Shen, Hengtao He +4

Terahertz ultra-massive MIMO (THz UM-MIMO) is envisioned as one of the key enablers of 6G wireless networks, for which channel estimation is highly challenging. Traditional analyti…

cs.CV2022

Attention Distraction: Watermark Removal Through Continual Learning with Selective Forgetting

Qi Zhong, Leo Yu Zhang, Shengshan Hu +3

Fine-tuning attacks are effective in removing the embedded watermarks in deep learning models. However, when the source data is unavailable, it is challenging to just erase the wat…

eess.IV2021

Sk-Unet Model with Fourier Domain for Mitosis Detection

Sen Yang, Feng Luo, Jun Zhang +1

Mitotic count is the most important morphological feature of breast cancer grading. Many deep learning-based methods have been proposed but suffer from domain shift. In this work,…

cs.CL2021★ 5 cited

Folden: -Fold Ensemble for Out-Of-Distribution Detection

Xiaoya Li, Jiwei Li, Xiaofei Sun +5

Out-of-Distribution (OOD) detection is an important problem in natural language processing (NLP). In this work, we propose a simple yet effective framework Folden, which mimics…

eess.IV2021★ 3 cited

Pyramidal Dense Attention Networks for Lightweight Image Super-Resolution

Huapeng Wu, Jie Gui, Jun Zhang +2

Recently, deep convolutional neural network methods have achieved an excellent performance in image superresolution (SR), but they can not be easily applied to embedded devices due…

eess.IV2021★ 1 cited

Feedback Pyramid Attention Networks for Single Image Super-Resolution

Huapeng Wu, Jie Gui, Jun Zhang +2

Recently, convolutional neural network (CNN) based image super-resolution (SR) methods have achieved significant performance improvement. However, most CNN-based methods mainly foc…