activity
20172022
most citedAttention-based Convolutional Neural Network for Weakly Labeled Human Activities Recognition with Wearable Sensors

206 citations · 241 across the 10 of their papers we have counts for

collaborators

15 papers

cs.CV2022

NTIRE 2022 Challenge on Efficient Super-Resolution: Methods and Results

Yawei Li, Kai Zhang, Radu Timofte +108

This paper reviews the NTIRE 2022 challenge on efficient single image super-resolution with focus on the proposed solutions and results. The task of the challenge was to super-reso…

cs.LG2022

Winograd Convolution: A Perspective from Fault Tolerance

Xinghua Xue, Haitong Huang, Cheng Liu +3

Winograd convolution is originally proposed to reduce the computing overhead by converting multiplication in neural network (NN) with addition via linear transformation. Other than…

cs.CV20221 cited

Fully Convolutional Change Detection Framework with Generative Adversarial Network for Unsupervised, Weakly Supervised and Regional Supervised Change Detection

Chen Wu, Bo Du, Liangpei Zhang

Deep learning for change detection is one of the current hot topics in the field of remote sensing. However, most end-to-end networks are proposed for supervised change detection,…

cs.CV20229 cited

Aerial Scene Parsing: From Tile-level Scene Classification to Pixel-wise Semantic Labeling

Yang Long, Gui-Song Xia, Liangpei Zhang +2

Given an aerial image, aerial scene parsing (ASP) targets to interpret the semantic structure of the image content, e.g., by assigning a semantic label to every pixel of the image.…

cs.CV2021

Transportation Density Reduction Caused by City Lockdowns Across the World during the COVID-19 Epidemic: From the View of High-resolution Remote Sensing Imagery

Chen Wu, Sihan Zhu, Jiaqi Yang +6

As the COVID-19 epidemic began to worsen in the first months of 2020, stringent lockdown policies were implemented in numerous cities throughout the world to control human transmis…

cs.LG202113 cited

LocalDrop: A Hybrid Regularization for Deep Neural Networks

Ziqing Lu, Chang Xu, Bo Du +3

In neural networks, developing regularization algorithms to settle overfitting is one of the major study areas. We propose a new approach for the regularization of neural networks…