7 citations · 13 across the 7 of their papers we have counts for
5 papers · 1 filter
MFogHub: Bridging Multi-Regional and Multi-Satellite Data for Global Marine Fog Detection and Forecasting
Mengqiu Xu, Kaixin Chen, Heng Guo +5
Deep learning approaches for marine fog detection and forecasting have outperformed traditional methods, demonstrating significant scientific and practical importance. However, the…
M4Fog: A Global Multi-Regional, Multi-Modal, and Multi-Stage Dataset for Marine Fog Detection and Forecasting to Bridge Ocean and Atmosphere
Mengqiu Xu, Ming Wu, Kaixin Chen +11
Marine fog poses a significant hazard to global shipping, necessitating effective detection and forecasting to reduce economic losses. In recent years, several machine learning (ML…
Adaptive Patch Exiting for Scalable Single Image Super-Resolution
Shizun Wang, Jiaming Liu, Kaixin Chen +3
Since the future of computing is heterogeneous, scalability is a crucial problem for single image super-resolution. Recent works try to train one network, which can be deployed on…
SamplingAug: On the Importance of Patch Sampling Augmentation for Single Image Super-Resolution
Shizun Wang, Ming Lu, Kaixin Chen +4
With the development of Deep Neural Networks (DNNs), plenty of methods based on DNNs have been proposed for Single Image Super-Resolution (SISR). However, existing methods mostly t…
CNNPruner: Pruning Convolutional Neural Networks with Visual Analytics
Guan Li, Junpeng Wang, Han-Wei Shen +3
Convolutional neural networks (CNNs) have demonstrated extraordinarily good performance in many computer vision tasks. The increasing size of CNN models, however, prevents them fro…